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VERB: verb

The tag VERB covers PTB tags VB, VBP, VBZ, VBD, VBG, VBN, except for auxiliary verb uses of be, have, do, and get.

(Auxiliary verbs and modals are AUX and the infinitive to is PART.)

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Treebank Statistics (UD_English)

There are 2025 VERB lemmas (11%), 3780 VERB types (18%) and 25845 VERB tokens (11%). Out of 17 observed tags, the rank of VERB is: 4 in number of lemmas, 3 in number of types and 3 in number of tokens.

The 10 most frequent VERB lemmas: have, be, get, go, do, say, know, make, take, want

The 10 most frequent VERB types: have, get, know, is, had, do, go, said, want, see

The 10 most frequent ambiguous lemmas: have (VERB 1501, AUX 1406), be (AUX 7716, VERB 876, NOUN 2, X 1), get (VERB 668, AUX 39), go (VERB 667, NOUN 3, PROPN 1), do (AUX 1019, VERB 618, NOUN 2, PROPN 1), say (VERB 506, INTJ 4), know (VERB 484, NOUN 1, ADV 1), take (VERB 440, NOUN 7), see (VERB 336, NOUN 1), use (VERB 304, NOUN 23, ADJ 1, PRON 1)

The 10 most frequent ambiguous types: have (VERB 844, AUX 647), get (VERB 418, AUX 20), know (VERB 391, NOUN 1, ADV 1), is (AUX 2127, VERB 346, ADV 1, PRON 1), had (VERB 357, AUX 164), do (AUX 516, VERB 309, NOUN 2, PROPN 1, ADP 1), go (VERB 287, NOUN 3, PROPN 1), see (VERB 209, NOUN 1), going (VERB 216, ADJ 1), take (VERB 201, NOUN 7)

• have
  • VERB 844: I have .
  • AUX 647: I really have n’t thought about writing a book .
• get
  • VERB 418: And what do we get for this effort ?
  • AUX 20: And do you get charged for it ?
• know
  • VERB 391: That ‘s overstating it , I know .
  • NOUN 1: Soldiers with vital training and know - how are refusing to re-enlist .
  • ADV 1: If you are looking for authentic British meat pies , then look know further .
• is
  • AUX 2127: The hottest item on Christmas wish lists this year is nuclear weapons .
  • VERB 346: But sometimes , of course , when Z happens after X it is because of X .
  • ADV 1: Then the need to be mature , that is , old enough , and big enough to breed .
  • PRON 1: You do n’t think is was because of female nudes considering the nearly naked girls / women seen at pools and beaches and the completely naked manikins that show up in store windows in malls during changes in display ?
• had
  • VERB 357: When they saw a cartoon of their prophet , people had to die .
  • AUX 164: It had been eating dog food the whole time .
• do
  • AUX 516: And what do we get for this effort ?
  • VERB 309: My life is too complicated right now trying to do my job .
  • NOUN 2: We arrived Sunday at about 230 and found a do we really liked .
  • PROPN 1: The nearest towns to the site are Puerto Iguazu in Argentina , about 12 miles from the falls , and Foz do Iguaçu in Brazil , which is equally close .
  • ADP 1: Unfortunately , do to Mr. Lay ‘s schedule he will not be able to participate .
• go
  • VERB 287: i have to go to butt - fucking mississippi .
  • NOUN 3: They phoned the same day , confirmed it was the gearbox quoted me the job , I gave the go ahead .
  • PROPN 1: I would recommend go launcher or adw launcher .
• see
  • VERB 209: Ginny , Please see the attached guaranty .
  • NOUN 1: This is a major breakthrough in the animal intelligence field and a must see / hear for every animal intelligence enthusiast .
• going
  • VERB 216: 2005 is going to rock !
  • ADJ 1: Additional resources are being allocated and the situation is being closely monitored ( both for quarter end signoff and on going operations ) .
• take
  • VERB 201: Can you send me the data you used : I shall take a look at it .
  • NOUN 7: Simple , Quick take away .

Morphology

The form / lemma ratio of VERB is 1.866667 (the average of all parts of speech is 1.181137).

The 1st highest number of forms (13) was observed with the lemma “be”: ‘m, ‘s, am, are, be, been, being, is, m, s, was, were, ’s.

The 2nd highest number of forms (6) was observed with the lemma “bear”: bear, beared, bearing, bears, bore, born.

The 3rd highest number of forms (6) was observed with the lemma “know”: knew, know, knowing, known, knows, no.

VERB occurs with 6 features: en-feat/VerbForm (25840; 100% instances), en-feat/Tense (14101; 55% instances), en-feat/Mood (10305; 40% instances), en-feat/Number (2141; 8% instances), en-feat/Person (2127; 8% instances), en-feat/Voice (1319; 5% instances)

VERB occurs with 13 feature-value pairs: Mood=Imp, Mood=Ind, Number=Plur, Number=Sing, Person=1, Person=3, Tense=Past, Tense=Pres, VerbForm=Fin, VerbForm=Ger, VerbForm=Inf, VerbForm=Part, Voice=Pass

VERB occurs with 15 feature combinations. The most frequent feature combination is VerbForm=Inf (7915 tokens). Examples: have, get, know, do, go, make, take, see, like, find

Relations

VERB nodes are attached to their parents using 32 different relations: en-dep/root (8340; 32% instances), en-dep/advcl (3568; 14% instances), en-dep/conj (3374; 13% instances), en-dep/xcomp (2502; 10% instances), en-dep/ccomp (1948; 8% instances), en-dep/acl:relcl (1930; 7% instances), en-dep/acl (1580; 6% instances), en-dep/parataxis (1032; 4% instances), en-dep/amod (741; 3% instances), en-dep/csubj (298; 1% instances), en-dep/case (194; 1% instances), en-dep/appos (73; 0% instances), en-dep/compound (50; 0% instances), en-dep/aux:pass (44; 0% instances), en-dep/aux (31; 0% instances), en-dep/obj (20; 0% instances), en-dep/_ (19; 0% instances), en-dep/list (15; 0% instances), en-dep/nsubj (13; 0% instances), en-dep/advmod (11; 0% instances), en-dep/discourse (11; 0% instances), en-dep/obl (11; 0% instances), en-dep/mark (10; 0% instances), en-dep/fixed (8; 0% instances), en-dep/reparandum (7; 0% instances), en-dep/csubj:pass (4; 0% instances), en-dep/orphan (4; 0% instances), en-dep/cc (2; 0% instances), en-dep/obl:npmod (2; 0% instances), en-dep/compound:prt (1; 0% instances), en-dep/dep (1; 0% instances), en-dep/flat (1; 0% instances)

Parents of VERB nodes belong to 18 different parts of speech: VERB (10335; 40% instances), ROOT (8359; 32% instances), NOUN (4566; 18% instances), ADJ (1538; 6% instances), PRON (367; 1% instances), PROPN (283; 1% instances), ADV (196; 1% instances), DET (73; 0% instances), NUM (66; 0% instances), AUX (20; 0% instances), SYM (16; 0% instances), X (8; 0% instances), ADP (6; 0% instances), PART (6; 0% instances), INTJ (2; 0% instances), SCONJ (2; 0% instances), CCONJ (1; 0% instances), PUNCT (1; 0% instances)

1084 (4%) VERB nodes are leaves.

2182 (8%) VERB nodes have one child.

4744 (18%) VERB nodes have two children.

17835 (69%) VERB nodes have three or more children.

The highest child degree of a VERB node is 17.

Children of VERB nodes are attached using 44 different relations: en-dep/nsubj (13685; 15% instances), en-dep/punct (13622; 15% instances), en-dep/obj (11358; 12% instances), en-dep/obl (8578; 9% instances), en-dep/advmod (7535; 8% instances), en-dep/mark (7146; 8% instances), en-dep/aux (6547; 7% instances), en-dep/cc (3294; 4% instances), en-dep/advcl (3264; 4% instances), en-dep/conj (3205; 4% instances), en-dep/xcomp (3139; 3% instances), en-dep/ccomp (2382; 3% instances), en-dep/aux:pass (1496; 2% instances), en-dep/nsubj:pass (1276; 1% instances), en-dep/parataxis (893; 1% instances), en-dep/compound:prt (817; 1% instances), en-dep/discourse (569; 1% instances), en-dep/obl:tmod (523; 1% instances), en-dep/expl (502; 1% instances), en-dep/iobj (423; 0% instances), en-dep/obl:npmod (204; 0% instances), en-dep/csubj (114; 0% instances), en-dep/compound (108; 0% instances), en-dep/nummod (59; 0% instances), en-dep/vocative (58; 0% instances), en-dep/cop (30; 0% instances), en-dep/appos (29; 0% instances), en-dep/cc:preconj (24; 0% instances), en-dep/fixed (21; 0% instances), en-dep/reparandum (20; 0% instances), en-dep/acl:relcl (17; 0% instances), en-dep/det (17; 0% instances), en-dep/amod (16; 0% instances), en-dep/list (14; 0% instances), en-dep/goeswith (12; 0% instances), en-dep/orphan (9; 0% instances), en-dep/acl (7; 0% instances), en-dep/_ (6; 0% instances), en-dep/csubj:pass (5; 0% instances), en-dep/case (4; 0% instances), en-dep/nmod:poss (4; 0% instances), en-dep/nmod (3; 0% instances), en-dep/dep (2; 0% instances), en-dep/flat (1; 0% instances)

Children of VERB nodes belong to 17 different parts of speech: NOUN (18687; 21% instances), PRON (13963; 15% instances), PUNCT (13620; 15% instances), VERB (10337; 11% instances), AUX (8073; 9% instances), ADV (6773; 7% instances), PART (4796; 5% instances), PROPN (3794; 4% instances), SCONJ (3282; 4% instances), CCONJ (3280; 4% instances), ADJ (1880; 2% instances), ADP (1110; 1% instances), INTJ (504; 1% instances), NUM (380; 0% instances), DET (247; 0% instances), SYM (175; 0% instances), X (137; 0% instances)

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Treebank Statistics (UD_English-ESL)

There are 1 VERB lemmas (6%), 1 VERB types (6%) and 13583 VERB tokens (15%). Out of 17 observed tags, the rank of VERB is: 16 in number of lemmas, 16 in number of types and 2 in number of tokens.

The 10 most frequent VERB lemmas: _

The 10 most frequent VERB types: _

The 10 most frequent ambiguous lemmas: _ (NOUN 14135, VERB 13583, PRON 9575, DET 9068, PUNCT 8624, ADP 7769, ADJ 5278, ADV 5121, AUX 4111, PART 3169, CONJ 2865, SCONJ 2278, PROPN 1574, NUM 776, INTJ 67, X 60, SYM 37)

The 10 most frequent ambiguous types: _ (NOUN 14135, VERB 13583, PRON 9575, DET 9068, PUNCT 8624, ADP 7769, ADJ 5278, ADV 5121, AUX 4111, PART 3169, CONJ 2865, SCONJ 2278, PROPN 1574, NUM 776, INTJ 67, X 60, SYM 37)

• _
  • NOUN 14135: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
  • VERB 13583: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
  • PRON 9575: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
  • DET 9068: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
  • PUNCT 8624: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
  • ADP 7769: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
  • ADJ 5278: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
  • ADV 5121: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
  • AUX 4111: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
  • PART 3169: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
  • CONJ 2865: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
  • SCONJ 2278: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
  • PROPN 1574: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
  • NUM 776: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
  • INTJ 67: _ _ _ _ _ _ _ _ _ _ _ _
  • X 60: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
  • SYM 37: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

Morphology

The form / lemma ratio of VERB is 1.000000 (the average of all parts of speech is 1.000000).

The 1st highest number of forms (1) was observed with the lemma “_”: _.

VERB does not occur with any features.

Relations

VERB nodes are attached to their parents using 30 different relations: en-dep/root (3359; 25% instances), en-dep/cop (2547; 19% instances), en-dep/advcl (1861; 14% instances), en-dep/xcomp (1725; 13% instances), en-dep/conj (1427; 11% instances), en-dep/ccomp (804; 6% instances), en-dep/acl:relcl (747; 5% instances), en-dep/acl (436; 3% instances), en-dep/parataxis (317; 2% instances), en-dep/csubj (182; 1% instances), en-dep/case (46; 0% instances), en-dep/amod (33; 0% instances), en-dep/nmod (18; 0% instances), en-dep/csubjpass (16; 0% instances), en-dep/dobj (15; 0% instances), en-dep/advmod (9; 0% instances), en-dep/nsubj (9; 0% instances), en-dep/discourse (8; 0% instances), en-dep/compound (5; 0% instances), en-dep/appos (4; 0% instances), en-dep/reparandum (4; 0% instances), en-dep/list (2; 0% instances), en-dep/mwe (2; 0% instances), en-dep/aux (1; 0% instances), en-dep/cc (1; 0% instances), en-dep/det (1; 0% instances), en-dep/goeswith (1; 0% instances), en-dep/mark (1; 0% instances), en-dep/nsubjpass (1; 0% instances), en-dep/remnant (1; 0% instances)

Parents of VERB nodes belong to 14 different parts of speech: VERB (5005; 37% instances), ROOT (3359; 25% instances), ADJ (2389; 18% instances), NOUN (2285; 17% instances), PRON (160; 1% instances), PROPN (132; 1% instances), ADV (129; 1% instances), NUM (75; 1% instances), DET (19; 0% instances), AUX (12; 0% instances), SYM (7; 0% instances), ADP (6; 0% instances), X (3; 0% instances), PART (2; 0% instances)

2738 (20%) VERB nodes are leaves.

971 (7%) VERB nodes have one child.

2312 (17%) VERB nodes have two children.

7562 (56%) VERB nodes have three or more children.

The highest child degree of a VERB node is 21.

Children of VERB nodes are attached using 40 different relations: en-dep/nsubj (6799; 17% instances), en-dep/punct (5605; 14% instances), en-dep/dobj (4775; 12% instances), en-dep/mark (3950; 10% instances), en-dep/nmod (3854; 9% instances), en-dep/aux (3213; 8% instances), en-dep/advmod (2536; 6% instances), en-dep/xcomp (1915; 5% instances), en-dep/advcl (1599; 4% instances), en-dep/cc (1392; 3% instances), en-dep/conj (1358; 3% instances), en-dep/ccomp (1108; 3% instances), en-dep/neg (659; 2% instances), en-dep/auxpass (448; 1% instances), en-dep/nsubjpass (369; 1% instances), en-dep/expl (321; 1% instances), en-dep/parataxis (283; 1% instances), en-dep/nmod:tmod (214; 1% instances), en-dep/iobj (179; 0% instances), en-dep/compound:prt (174; 0% instances), en-dep/nmod:npmod (64; 0% instances), en-dep/discourse (59; 0% instances), en-dep/det (44; 0% instances), en-dep/csubj (33; 0% instances), en-dep/csubjpass (27; 0% instances), en-dep/cop (24; 0% instances), en-dep/case (22; 0% instances), en-dep/mwe (21; 0% instances), en-dep/amod (12; 0% instances), en-dep/nmod:poss (11; 0% instances), en-dep/vocative (8; 0% instances), en-dep/cc:preconj (4; 0% instances), en-dep/compound (3; 0% instances), en-dep/det:predet (2; 0% instances), en-dep/list (2; 0% instances), en-dep/acl:relcl (1; 0% instances), en-dep/appos (1; 0% instances), en-dep/goeswith (1; 0% instances), en-dep/nummod (1; 0% instances), en-dep/reparandum (1; 0% instances)

Children of VERB nodes belong to 17 different parts of speech: NOUN (8313; 20% instances), PRON (7507; 18% instances), PUNCT (5604; 14% instances), VERB (5005; 12% instances), AUX (3667; 9% instances), ADV (2844; 7% instances), PART (2667; 6% instances), SCONJ (1711; 4% instances), CONJ (1393; 3% instances), ADJ (986; 2% instances), PROPN (540; 1% instances), DET (350; 1% instances), ADP (276; 1% instances), NUM (161; 0% instances), INTJ (52; 0% instances), SYM (12; 0% instances), X (4; 0% instances)

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Treebank Statistics (UD_English-LinES)

There are 1 VERB lemmas (6%), 2218 VERB types (25%) and 8020 VERB tokens (12%). Out of 17 observed tags, the rank of VERB is: 16 in number of lemmas, 2 in number of types and 3 in number of tokens.

The 10 most frequent VERB lemmas: _

The 10 most frequent VERB types: was, said, do, know, had, have, is, see, going, made

The 10 most frequent ambiguous lemmas: _ (NOUN 12161, PUNCT 8085, VERB 8020, ADP 6788, DET 6429, PRON 6303, ADJ 4270, ADV 3700, AUX 3539, PROPN 2257, CCONJ 2081, PART 1703, SCONJ 1231, NUM 462, INTJ 122, X 41, SYM 5)

The 10 most frequent ambiguous types: was (AUX 582, VERB 181), said (VERB 165, ADJ 1), do (VERB 104, AUX 29), had (AUX 372, VERB 87), have (AUX 120, VERB 75), is (AUX 366, VERB 73), got (VERB 45, AUX 2), get (VERB 42, AUX 1), want (VERB 43, AUX 4), are (AUX 173, VERB 39)

• was
  • AUX 582: I was just wondering if you liked the book .
  • VERB 181: He wondered if the young Auster had been any better at it than he was .
• said
  • VERB 165: Quinn smiled weakly . No problem , he said .
  • ADJ 1: As you know , underage wizards are not permitted to perform spells outside school , and further spellwork on your part may lead to expulsion from said school ( Decree for the Reasonable Restriction of Underage Sorcery , 1875 , Paragraph C ) .
• do
  • VERB 104: I wish it was . But this has nothing to do with literature .
  • AUX 29: If you do n’t like it , why do you go on reading ?
• had
  • AUX 372: He wondered if the young Auster had been any better at it than he was .
  • VERB 87: Quinn had trouble finding a seat .
• have
  • AUX 120: If I had been in your place , I probably would have done the same thing .
  • VERB 75: Each filter you apply is added to the ones you already have in effect .
• is
  • AUX 366: Each filter you apply is added to the ones you already have in effect .
  • VERB 73: Click the blue arrow to see the filter that is in effect .
• got
  • VERB 45: I ‘m afraid you ‘ve got the wrong Paul Auster .
  • AUX 2: You ‘ve got to be kidding , they ‘ll talk your head off . “
• get
  • VERB 42: We soon get around to contemporary matters .
  • AUX 1: The only real feeling was a desire to get appointed to a trading-post where ivory was to be had , so that they could earn percentages .
• want
  • VERB 43: I want you to have it .
  • AUX 4: That is what I want to talk about today .
• are
  • AUX 173: What are XML schemas
  • VERB 39: Identifying filters that are currently in effect

Morphology

The form / lemma ratio of VERB is 2218.000000 (the average of all parts of speech is 527.705882).

The 1st highest number of forms (2218) was observed with the lemma “_”: ‘d, ‘m, ‘re, ‘s, ‘ve, Anticipating, Autofiltering, Baking, Charm, Chart, Click, Combining, Converting, Cursed, Dash, Default, Dunno, Failing, Gasping, Gazing, Gliding, Insert, Judging, Linking, Pardon, Position, Sends, Shrugging, Stapled, Stepping, Supermechanized, Supposing, Th-thank, abandon, abandoned, abate, abolished, absorb, abuses, accelerated, accept, accepted, access, accessing, accompanied, accomplish, accomplished, account, accounts, accumulating, accused, accustomed, achieve, achieving, aching, acknowledge, acknowledged, acquainted, act, acted, activate, activates, acts, add, added, adding, address, addresses, addressing, admired, admit, admitting, adopted, advance, advanced, advancing, advertise, advise, advises, affect, affected, affects, affronted, agree, agreed, agreeing, agrees, aim, aimed, aims, align, allow, allowed, allowing, allows, alternated, alternating, am, amending, amounted, amused, amusing, analyze, analyzing, anchored, angered, annoyed, annulled, answer, answered, answering, answers, anticipate, apologized, apologizing, appalled, appalling, appeal, appealed, appear, appeared, appears, append, applied, applies, apply, applying, appointed, appointing, appreciate, approached, approaching, approved, approving, are, argue, argued, arising, armed, arose, aroused, arranged, arranging, arrive, arrived, arrives, arriving, ask, asked, asking, asks, associated, assume, assumed, assumes, assure, assured, assuring, astonished, ate, attached, attack, attend, attended, autograph, avoid, avoided, avoiding, await, awaited, backbiting, backed, backtracked, baffled, baked, balance, balanced, balancing, banging, banished, banning, bared, baring, barred, based, be, beamed, bear, bearded, bearing, beat, beaten, became, become, becomes, becoming, befriend, began, begged, begin, beginning, begins, beguiled, begun, behaved, behaving, believe, believed, believes, believing, belong, belonged, benefit, bent, bewitched, biased, bid, biding, bind, blamed, blazed, blending, blew, blinked, block, blocked, bloomed, blown, blundered, blurred, boast, bolted, bombard, bordered, borne, borrow, borrowed, bother, bothered, bought, bound, bounded, bounding, bow, bowed, braced, brag, break, breaking, breathing, bring, bringing, brings, broke, broken, brooding, brought, bruised, brushed, brushing, brutalizing, build, building, built, bulging, bump, bundled, burden, burning, burst, buttered, buttering, buttressed, buy, buys, buzzed, buzzing, calculate, calculated, call, called, calling, calls, came, canopied, care, carried, carries, carry, carrying, cash, catch, caught, caused, ceased, change, changed, changes, changing, characterized, charmed, chatted, chattering, check, checks, cheered, chill, chiseled, choose, choosing, chose, chosen, christening, churning, civilize, claimed, clamouring, clanged, clapped, clattered, clattering, clean, cleaned, cleaning, clear, cleared, clears, clicked, climb, climbed, clinging, clinking, closed, closing, clustered, clutching, cluttered, codifies, collapse, collapsed, collected, collecting, collided, combating, come, comes, comforted, coming, commands, commented, communicate, communicated, communicating, compare, compared, compel, complete, completed, complicated, complicating, compliment, comply, concentrate, concentrates, concerned, concerning, concerns, conclude, concludes, concluding, condemn, conducting, conferred, confess, configures, confine, confirm, confirmed, conform, conforms, confronted, congratulate, connect, connected, connects, consent, consider, considered, consist, consisted, consists, constitute, consult, consume, contact, contain, contained, containing, contains, contempt, continue, continued, contribute, contributed, control, convert, converted, converts, conveyed, convict, cook, cooked, cooking, cooperating, coordinating, copied, copy, copying, corrected, corresponding, cost, coughed, count, counter, counting, cover, covered, covering, cowered, cracked, crackling, crashed, crashing, crawl, creaks, create, created, creates, creating, cried, cries, crippled, criticise, cropped, cropping, crossed, crosses, crossing, crouched, crumbles, curled, curving, customizing, cut, cutting, cycled, d’, damage, dance, danced, dancing, dangling, dare, daring, darkening, dart, darted, dashed, dazzling, de-gnoming, deafening, deal, dealing, deals, dealt, debated, decide, decided, decipher, declared, declaring, declined, decrease, define, defined, defines, deformed, delete, deleted, delighted, delimit, deliver, delivered, delivering, demanded, demands, denied, denoted, denounced, deny, departed, departs, depending, depends, deploying, depopulated, deported, deposit, derived, descended, describe, described, describes, describing, deserted, deserve, design, designed, designing, destined, destroyed, detain, deteriorate, determines, develop, developed, developing, develops, devised, devoted, dial, dialed, dialing, dials, did, die, died, digested, digging, dined, dipped, directing, disabled, disappear, disappeared, disappointed, disclaim, discounted, discover, discovered, discuss, discussed, discussing, disintegrate, dislike, dismissed, disperse, display, displayed, displaying, displays, disrupt, disrupted, dissembling, dissipated, dissolve, distinguish, distorted, distract, distribute, distributed, distributing, disturb, disturbed, disturbing, disturbs, dived, divine, do, documents, dodging, does, doing, done, donning, doubt, doubts, downloaded, dozed, drag, dragged, dragging, drank, draping, draw, drawing, drawn, dream, dreaming, dredge, drenched, dress, dressed, drew, drift, drifted, drifting, drink, drinking, drip, driven, drives, driving, drizzled, droning, drooped, drop, dropped, drove, drowned, drowning, drumming, drying, duck, ducked, dug, dwell, dying, earn, earned, ease, eased, eat, eat-e, eaten, eating, edging, edit, effaced, effacing, elapsed, electioneering, elicited, eliminate, eliminated, elude, eluded, embarked, embarrass, embedded, embrace, embraced, emerged, emerges, emigrate, emitted, emphasize, employed, employs, emptied, enable, enabled, enables, encompasses, encompassing, encountering, encourage, encouraged, encroaches, end, endanger, endangering, ended, ending, endorse, endorsed, enfiladed, engage, engaging, engineered, enhance, enjoy, enjoyed, enjoying, enrich, ensconced, ensure, ensures, ensuring, entangled, enter, entered, entering, entitled, entrenched, enveloping, erect, escape, escaped, establish, established, establishing, estimated, etched, evoke, evolving, examine, examined, examining, excepted, exchange, exchanged, exchanging, exclaimed, exclaiming, excuse, excused, excuses, exempt, exert, exhibited, exiled, exist, existed, exists, expect, expected, expecting, expel, experience, expires, explain, explained, exploding, export, exporting, exposed, express, expressed, expunging, extended, extract, extrudes, exulting, face, faces, facing, faded, fading, failed, fall, fallen, falling, faltered, fancied, fancy, fascinated, fastened, fated, favour, feared, feature, fed, feed, feel, feeling, feels, fell, felt, fend, fetch, feted, fidgeted, fighting, files, fill, filled, filling, filter, filtered, filtering, find, finding, finds, finish, finished, firing, fishing, fit, fitted, fix, fixed, flapped, flaring, flashing, flattened, flay, fled, flew, flexed, flicked, flicker, flinched, flinching, flirt, floated, floating, flooded, flooding, flow, flung, flushed, fly, flying, focus, focusing, folded, follow, followed, following, follows, force, forced, forcing, foresaw, forget, forgive, forgot, forgotten, form, format, formed, forming, fought, found, framed, freed, fringed, frisked, frowning, furnished, fuss, fussed, gain, gained, galloping, gardened, gasped, gather, gathered, gathering, gave, gaze, gazed, generate, generated, gesticulating, gestured, get, gets, getting, gibbering, give, given, gives, giving, glanced, glancing, glared, gleaming, glide, glided, glimmering, glisten, glistening, gloated, glorified, gloss, glowered, glowing, go, goes, goggle, goggled, goggling, going, gone, got, governed, governing, grabbed, grabbing, granted, grants, grasp, grasped, grasping, gravitated, greeted, greeting, grew, grieving, grinned, grinning, gripped, groan, groaned, ground, group, grouped, grouping, grow, growing, growled, grown, grows, grudging, grumbling, grunt, guarantees, guard, guarding, guess, guessed, gulped, had, haggle, hailed, half-dressed, half-embarrassed, hammered, hamper, hand, handed, handing, handled, handling, hang, hanged, hanging, hankering, happen, happened, happening, happens, harbouring, harvesting, has, hastened, hatched, hated, hauled, haunt, have, head, headed, hear, heard, hearing, heartening, heated, heave, heightened, held, help, helping, heralding, hidden, hide, highlighted, hindering, hint, hiring, hit, hitched, hoisted, hold, holding, holed, honking, hope, hoped, hoping, house, hover, hovered, howled, hugged, hunched, hung, hurried, hurt, identify, identifying, ignore, ignored, imagine, imagined, impart, imparting, implement, implemented, implementing, implies, import, imported, importing, imposed, improve, improving, incapacitated, include, included, includes, including, increase, increasing, incur, indexing, indicate, indicated, indicates, indulge, indulged, influence, influenced, informed, inherit, initiate, injected, insist, insisted, insisting, inspecting, inspired, install, installed, installing, instructed, instructing, insure, intend, intended, intensified, interact, interested, interpreted, interprets, interrupted, intrigued, intriguing, introduce, introduced, introducing, intrusted, invaded, invading, invest, invited, inviting, involve, involved, involving, ironing, is, jangling, jeopardised, jerked, jingling, join, joined, joining, jostling, judged, jumped, jumping, justified, justify, keep, keeping, keeps, kept, kicked, kicking, kidding, kill, killed, knew, knit, knitting, knock, knocked, knocking, know, knowing, known, knows, lacking, lacks, laid, land, landed, landing, lapped, lasping, last, lasted, lathered, laugh, laughed, laughing, lay, laying, lead, leading, leads, leaned, leaning, leaped, leapt, learn, learned, learning, leave, leaves, leaving, lecturing, led, leered, left, legitimated, lengthening, lengthens, lent, let, lets, letting, level, levy, liberalize, license, licensing, lie, lies, lifted, lifting, light, lighted, like, liked, likes, limit, limited, lined, link, linked, listed, listen, listened, listening, listens, listing, lists, lit, littered, live, lived, living, loads, loafing, located, locked, locking, logged, loitering, lolled, longing, look, looked, looking, looks, loomed, lording, lose, losing, lost, love, loves, lulling, lurching, lying, made, magic, maintain, maintained, maintains, make, makes, making, maligned, manage, managed, manipulate, manipulating, mapped, march, marching, marked, marking, married, marvelled, match, matched, matches, matter, mattered, mean, meaning, means, meant, measure, measured, meet, meeting, mend, mentioned, mentions, met, mind, minded, mingle, mingled, misguided, misinterpreted, miss, missed, missing, misunderstood, mixed, mixing, modified, modify, monitoring, mopped, mounted, move, moved, moving, mowed, muddle, mumble, mumbled, murmured, muster, muttered, muttering, nailed, named, names, naming, narrow, need, needed, needing, needs, negotiate, nodded, note, noted, notice, noticed, nudge, obeyed, obliged, obscured, observe, observed, observes, obsess, obtained, occupied, occupy, occupying, occur, occurred, offended, offer, offered, offering, offers, oiled, oozing, open, opened, opening, opens, opposed, orchestrated, ordered, organizing, originated, ornamented, outlaw, overcome, overlap, overlooked, overrides, overrun, overtaking, overthrow, overwrite, owed, owned, packed, packing, paddled, padlocked, paid, panted, panting, paraded, paraphrase, parked, part, parted, pass, passed, passes, passing, paste, patting, paused, pausing, pay, paying, peaked, pecking, peer, peered, penalise, penalised, peopled, perceived, perched, perching, perform, performing, perked, permitted, perpetuated, persisted, persisting, persists, personified, persuade, persuading, pervading, petition, pick, picked, picking, piece, piloted, pitied, place, placed, planning, planting, play, played, playing, please, pleased, pleasure-seeking, plot, plotting, plugs, plunged, plying, point, pointed, pointing, poised, polish, politisized, pollutes, poring, positing, possessed, post, posted, postponed, pounded, pouring, practicing, practise, practised, praised, prayed, praying, preaching, predetermined, predict, preoccupied, prepared, preparing, present, presented, preserve, press, pressed, presses, pretended, pretending, prevail, prevent, preventing, prevents, print, probe, proclaimed, produce, produced, produces, producing, projected, promise, promised, promote, prompted, pronounced, proposed, proposes, propped, protect, protecting, protects, protested, prove, provide, provided, provides, providing, provoke, provoked, pruned, published, pull, pulled, pulling, pumped, pumping, punch, pursed, pursuing, pushed, pushing, put, puts, putting, puzzled, questioned, queueing, quickened, quickening, quitted, quivered, quoted, quotes, quoth, raced, racing, raided, rail, rained, rains, raise, raised, raising, ran, rang, rattled, reach, reached, reaches, reaching, read, reading, reads, realised, realize, realized, realizing, reap, reappeared, reappearing, reapplying, rearrange, reasoned, reassured, recall, recalled, receded, receive, received, receives, recited, reckon, reclaimed, reclined, recognises, recognize, recognized, recognizes, recoils, recommended, recommending, recommends, record, recorded, recover, recreate, rectified, redeems, reduce, reduced, reducing, refer, reference, referencing, referred, referring, refers, refilled, reflect, reflected, reflects, refreshed, refreshing, refurbish, refuse, refused, regain, regarded, regards, register, regret, regulate, regulated, reimbursed, rejected, rejecting, related, relearned, relied, relieved, relinquished, remain, remained, remains, remarked, remember, remembered, remembering, remerged, remind, reminded, remove, removed, removes, removing, rename, reopen, repainted, repaired, repeated, rephrasing, replaced, reply, report, reported, reports, reposed, represent, represented, request, require, required, requiring, resembled, resembling, reserve, resides, resist, resisting, resize, respect, respected, respects, respond, responded, rested, resting, restricted, restructure, resulted, results, resumed, retable, retailing, retain, retained, retest, retraced, retreat, return, returned, returning, returns, reversed, revert, review, reviews, revisited, revved, rewinding, rewrite, rewriting, ride, riding, ringing, rinse, rioted, rise, risen, risk, roared, roaring, robbed, rocked, rocking, rode, rolled, rolling, romped, rose, rotting, rounded, ruffled, ruinin’, rumbling, run, running, runs, rush, rushing, rusting, sacrificed, safeguards, said, sailed, sails, salute, saluted, sang, sank, sat, satisfied, save, saved, saves, saving, saw, say, saying, says, scare, scattered, scattering, scavenging, scented, scored, scorning, scrambling, scrape, scraping, scratched, scratching, screamed, screeching, screwing, scrubbing, scrutinizing, sealed, searched, searches, searching, seated, secure, see, seeing, seeking, seem, seemed, seems, seen, seeping, sees, seized, seizing, select, selected, selecting, self-contained, self-dispersed, sell, selling, send, sending, sensing, sent, separated, separates, separating, serve, served, set, setting, settled, sewn, shadowed, shake, shaking, shaped, share, shared, sharing, shatter, shattered, shave, shaved, shelling, sheltered, shied, shifted, shine, shining, shipped, shone, shooed, shook, shoot, shop, shorn, shot, shout, shouted, shouting, shoved, show, showed, showered, showing, shown, shows, shrinking, shrug, shrugged, shuddered, shuffled, shuffling, shut, sickened, sighed, sign, signalled, signed, signified, signing, simplifies, sing, singing, sink, sinking, sit, sits, sitting, sizzling, skimming, skulking, slammed, slamming, slandered, slapping, sleep, slept, slid, slight, slip, slipped, slipping, slips, slouched, slow, slowing, slumped, slurped, smell, smile, smiled, smiles, smiling, smirking, smoke, smoked, smoking, smooth, smoothing, smuggling, snaking, snatched, sneaked, sneaking, sniffed, snoozing, snored, so-called, soared, softened, sold, solve, solved, sort, sorting, sound, sounded, sounding, sounds, spaced, speak, speaking, speaks, specified, specifies, specify, specifying, sped, spell, spending, spent, spew, spilling, spin, spinning, splattered, split, spoiled, spoke, spoken, sport, spotted, spouting, sprang, sprawled, sprayed, spread, spreading, sprinted, sprinting, sprung, squeezed, squinting, stabbed, stacked, stagger, stand, standing, stands, stared, staring, start, started, starting, starve, starving, stated, states, stay, stayed, steadied, steal, stealing, steered, step, stepped, sticking, stiffening, sting, stir, stirred, stirring, stirs, stomach, stood, stoop, stooped, stop, stopped, stopping, stops, store, stored, stores, storm, straightened, straining, straw, streamed, strengthen, stretched, stretching, stricken, strike, striking, strive, strode, stroll, strolled, strolling, struck, structure, structured, struggled, strutting, stuck, studied, studying, stumbled, submit, substitute, subvert, succeeded, sucked, suffering, suffices, suggest, suggests, suited, summarising, summoned, sunk, sunken, supplying, support, supported, supporting, supports, suppose, supposed, suppress, surging, surprise, surprised, surprising, surrendering, surrounded, surrounding, survived, suspect, suspected, suspended, swallow, swallowed, swap, swayed, swaying, sweep, sweeping, swept, swinging, switch, swooped, swung, tabled, tackle, take, take-out, taken, takes, taking, talk, talked, talking, talks, tapering, tapped, tattoed, taught, taunting, teaching, tear, tearing, televised, televising, tell, telling, tells, tend, tender, tending, test, thank, thanking, thickened, think, thinking, thinks, thinning, thought, thought-nourishing, thrashing, threatening, thresh, threw, thrilling, throbbing, throw, throwing, thrown, thrusting, tied, tinkering, tipped, titled, toasted, toasting, toiling, told, tolerate, took, tooted, tore, toss, tossed, touch, touched, touching, toying, traces, trade, training, tramping, transform, transformed, transforming, transforms, translated, treat, treated, treating, trembling, tried, tries, trimmed, tripping, troubled, trust, try, trying, tucked, tumbled, turn, turned, turning, turns, twiddled, twirl, unbound, unchanged, uncoiled, undergo, underlined, underlying, underpin, understand, understanding, understood, unexpected, unfold, unhooked, unknown, unlocking, unnoticed, unravelling, unremarked, untitled, updating, uphold, upsets, upsetting, upsizing, urge, use, used, uses, using, usurp, validated, vanish, vanished, vanishing, vary, veiled, ventured, verifies, view, visited, visiting, vote, voted, voting, wagged, waggled, wait, waited, waiting, wake, waking, walk, walked, walking, wallowing, wander, wandered, wandering, waning, want, wanted, wanting, wants, ward, warmed, warned, was, wash, washed, wasted, wasting, watch, watched, watching, watered, waved, wavered, waving, weakening, weaning, wear, wearing, wedged, wedging, weighed, welcome, welcomed, welcomes, welded, went, wept, were, wheeled, whine, whipped, whipping, whisked, whispered, whispering, whitened, willed, wine-growing, wined, winking, wiped, wish, wished, wishes, wishing, withdrawing, withdrawn, woke, woken, won, wonder, wondered, wondering, wonders, wore, work, worked, working, works, worn, worried, worry, wound, wounded, wrapped, wrecked, write, writes, writhe, writing, written, wrote, yawned, yawning, yelling, yield, zigzagged.

VERB does not occur with any features.

Relations

VERB nodes are attached to their parents using 19 different relations: en-dep/root (2883; 36% instances), en-dep/conj (1325; 17% instances), en-dep/advcl (1142; 14% instances), en-dep/xcomp (635; 8% instances), en-dep/acl:relcl (468; 6% instances), en-dep/amod (394; 5% instances), en-dep/acl (366; 5% instances), en-dep/ccomp (340; 4% instances), en-dep/csubj (124; 2% instances), en-dep/aux (106; 1% instances), en-dep/appos (75; 1% instances), en-dep/parataxis (64; 1% instances), en-dep/dislocated (40; 0% instances), en-dep/obj (35; 0% instances), en-dep/advmod (7; 0% instances), en-dep/csubj:pass (6; 0% instances), en-dep/discourse (6; 0% instances), en-dep/obl:agent (3; 0% instances), en-dep/mark (1; 0% instances)

Parents of VERB nodes belong to 16 different parts of speech: VERB (3474; 43% instances), ROOT (2883; 36% instances), NOUN (1099; 14% instances), ADJ (289; 4% instances), PRON (114; 1% instances), ADV (63; 1% instances), PROPN (38; 0% instances), AUX (28; 0% instances), ADP (20; 0% instances), NUM (4; 0% instances), INTJ (2; 0% instances), PART (2; 0% instances), CCONJ (1; 0% instances), DET (1; 0% instances), PUNCT (1; 0% instances), SCONJ (1; 0% instances)

190 (2%) VERB nodes are leaves.

759 (9%) VERB nodes have one child.

1427 (18%) VERB nodes have two children.

5644 (70%) VERB nodes have three or more children.

The highest child degree of a VERB node is 17.

Children of VERB nodes are attached using 33 different relations: en-dep/punct (5026; 17% instances), en-dep/nsubj (4488; 15% instances), en-dep/obl (3520; 12% instances), en-dep/obj (3075; 10% instances), en-dep/advmod (2556; 9% instances), en-dep/aux (2341; 8% instances), en-dep/mark (1856; 6% instances), en-dep/conj (1279; 4% instances), en-dep/advcl (1060; 4% instances), en-dep/cc (1024; 3% instances), en-dep/xcomp (1006; 3% instances), en-dep/nsubj:pass (465; 2% instances), en-dep/ccomp (344; 1% instances), en-dep/case (290; 1% instances), en-dep/compound:prt (286; 1% instances), en-dep/expl (158; 1% instances), en-dep/dislocated (102; 0% instances), en-dep/appos (99; 0% instances), en-dep/obl:agent (83; 0% instances), en-dep/discourse (79; 0% instances), en-dep/cop (75; 0% instances), en-dep/csubj (60; 0% instances), en-dep/iobj (58; 0% instances), en-dep/det (56; 0% instances), en-dep/parataxis (51; 0% instances), en-dep/vocative (43; 0% instances), en-dep/amod (32; 0% instances), en-dep/compound (15; 0% instances), en-dep/nmod:poss (11; 0% instances), en-dep/acl (7; 0% instances), en-dep/csubj:pass (6; 0% instances), en-dep/acl:relcl (3; 0% instances), en-dep/nummod (1; 0% instances)

Children of VERB nodes belong to 17 different parts of speech: NOUN (6578; 22% instances), PUNCT (5026; 17% instances), PRON (4296; 15% instances), VERB (3474; 12% instances), AUX (2353; 8% instances), ADV (2351; 8% instances), PART (1238; 4% instances), PROPN (1132; 4% instances), CCONJ (1028; 3% instances), SCONJ (933; 3% instances), ADJ (535; 2% instances), ADP (400; 1% instances), NUM (72; 0% instances), INTJ (69; 0% instances), DET (62; 0% instances), X (5; 0% instances), SYM (3; 0% instances)

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Treebank Statistics (UD_English-ParTUT)

There are 928 VERB lemmas (16%), 1529 VERB types (22%) and 3600 VERB tokens (9%). Out of 17 observed tags, the rank of VERB is: 3 in number of lemmas, 2 in number of types and 5 in number of tokens.

The 10 most frequent VERB lemmas: have, be, make, include, take, write, use, like, give, do

The 10 most frequent VERB types: have, is, like, make, has, made, wrote, including, based, take

The 10 most frequent ambiguous lemmas: have (AUX 248, VERB 89), be (AUX 1018, VERB 76), use (VERB 41, NOUN 17), like (VERB 38, ADP 24, SCONJ 1, ADJ 1), do (AUX 52, VERB 33), need (VERB 29, NOUN 10), say (VERB 25, NOUN 2), find (VERB 22, NOUN 1), lead (VERB 22, NOUN 2), help (VERB 19, NOUN 2)

The 10 most frequent ambiguous types: have (AUX 106, VERB 39), is (AUX 320, VERB 38), like (VERB 34, ADP 21, ADJ 1, SCONJ 1), has (AUX 94, VERB 29), had (AUX 41, VERB 16), need (VERB 16, NOUN 7), set (VERB 13, NOUN 5, ADJ 2), use (NOUN 15, VERB 14), do (AUX 26, VERB 13), are (AUX 163, VERB 12)

• have
  • AUX 106: Decisions have also been adopted against a tax of this kind .
  • VERB 39: They also have a number of other important environmental impacts .
• is
  • AUX 320: The work is protected by copyright and / or other applicable law .
  • VERB 38: There is no room for amendments .
• like
  • VERB 34: I would like your advice about Rule 143 concerning inadmissibility .
  • ADP 21: Of course , federalism sounds like a good thing .
  • ADJ 1: 1831 saw the success of La Peau De Chagrin ( The Wild Ass ‘s Skin or The Magic skin ) , a fable - like tale about a despondent young man named Raphaël De Valentin who finds an animal skin which promises great power and wealth .
  • SCONJ 1: It inhales oxygen , just like we do .
• has
  • AUX 94: Transport safety has sadly been in the news recently :
  • VERB 29: Everyone has the right to freedom of thought , conscience and religion ;
• had
  • AUX 41: John Aubrey reported that Shakespeare had been a country schoolmaster .
  • VERB 16: We had these data a few years ago .
• need
  • VERB 16: Brazil and India need new growth models .
  • NOUN 7: Such consultation may highlight the need for a phased introduction or transitional measures .
• set
  • VERB 13: The conditions and arrangements for admission are set out in the Protocol annexed to this Treaty .
  • NOUN 5: Compelling policymakers to implement such policies will require a new set of skills that draws upon lessons from around the world .
  • ADJ 2: In 1613 , Sir Henry Wotton recorded that Henry VIII “ was set forth with many extraordinary circumstances of pomp and ceremony “ .
• use
  • NOUN 15: Facebook accounts are for individual use .
  • VERB 14: Does it cost money to use Facebook ?
• do
  • AUX 26: I do not think , however , that this report has come too late .
  • VERB 13: Thank you , Mr Segni , I shall do so gladly .
• are
  • AUX 163: Why are no - smoking areas not enforced ?
  • VERB 12: Why are there no fire instructions ?

Morphology

The form / lemma ratio of VERB is 1.647629 (the average of all parts of speech is 1.187751).

The 1st highest number of forms (8) was observed with the lemma “be”: ’s, are, be, been, being, is, was, were.

The 2nd highest number of forms (6) was observed with the lemma “have”: ad, h, had, has, have, having.

The 3rd highest number of forms (5) was observed with the lemma “begin”: began, begin, beginning, begins, begun.

VERB occurs with 5 features: en-feat/VerbForm (3600; 100% instances), en-feat/Tense (2399; 67% instances), en-feat/Mood (1327; 37% instances), en-feat/Person (975; 27% instances), en-feat/Number (936; 26% instances)

VERB occurs with 14 feature-value pairs: Mood=Imp, Mood=Ind, Mood=Sub, Number=Plur, Number=Sing, Person=1, Person=2, Person=3, Tense=Past, Tense=Pres, VerbForm=Fin, VerbForm=Ger, VerbForm=Inf, VerbForm=Part

VERB occurs with 28 feature combinations. The most frequent feature combination is Tense=Past|VerbForm=Part (887 tokens). Examples: based, made, given, taken, adopted, used, entitled, written, done, published

Relations

VERB nodes are attached to their parents using 18 different relations: en-dep/root (1197; 33% instances), en-dep/acl (609; 17% instances), en-dep/advcl (527; 15% instances), en-dep/conj (384; 11% instances), en-dep/acl:relcl (315; 9% instances), en-dep/xcomp (237; 7% instances), en-dep/ccomp (199; 6% instances), en-dep/csubj (78; 2% instances), en-dep/parataxis (22; 1% instances), en-dep/case (10; 0% instances), en-dep/amod (8; 0% instances), en-dep/nsubj (4; 0% instances), en-dep/csubj:pass (3; 0% instances), en-dep/fixed (2; 0% instances), en-dep/goeswith (2; 0% instances), en-dep/appos (1; 0% instances), en-dep/nmod (1; 0% instances), en-dep/nsubj:pass (1; 0% instances)

Parents of VERB nodes belong to 13 different parts of speech: VERB (1199; 33% instances), ROOT (1197; 33% instances), NOUN (936; 26% instances), ADJ (157; 4% instances), PRON (51; 1% instances), PROPN (32; 1% instances), ADV (13; 0% instances), NUM (5; 0% instances), AUX (4; 0% instances), CCONJ (3; 0% instances), DET (1; 0% instances), PUNCT (1; 0% instances), SYM (1; 0% instances)

137 (4%) VERB nodes are leaves.

357 (10%) VERB nodes have one child.

657 (18%) VERB nodes have two children.

2449 (68%) VERB nodes have three or more children.

The highest child degree of a VERB node is 13.

Children of VERB nodes are attached using 38 different relations: en-dep/punct (1960; 15% instances), en-dep/obl (1773; 14% instances), en-dep/nsubj (1699; 13% instances), en-dep/obj (1571; 12% instances), en-dep/mark (1060; 8% instances), en-dep/advmod (881; 7% instances), en-dep/aux (825; 6% instances), en-dep/advcl (450; 4% instances), en-dep/cc (391; 3% instances), en-dep/conj (369; 3% instances), en-dep/xcomp (355; 3% instances), en-dep/aux:pass (340; 3% instances), en-dep/nsubj:pass (339; 3% instances), en-dep/ccomp (257; 2% instances), en-dep/obl:agent (117; 1% instances), en-dep/compound:prt (62; 0% instances), en-dep/expl (60; 0% instances), en-dep/nummod (37; 0% instances), en-dep/amod (35; 0% instances), en-dep/vocative (31; 0% instances), en-dep/iobj (26; 0% instances), en-dep/cop (23; 0% instances), en-dep/csubj (21; 0% instances), en-dep/parataxis (20; 0% instances), en-dep/case (12; 0% instances), en-dep/nmod:npmod (8; 0% instances), en-dep/appos (7; 0% instances), en-dep/fixed (7; 0% instances), en-dep/nmod (6; 0% instances), en-dep/csubj:pass (3; 0% instances), en-dep/det (3; 0% instances), en-dep/discourse (3; 0% instances), en-dep/acl:relcl (2; 0% instances), en-dep/dislocated (2; 0% instances), en-dep/nmod:poss (2; 0% instances), en-dep/compound (1; 0% instances), en-dep/dep (1; 0% instances), en-dep/goeswith (1; 0% instances)

Children of VERB nodes belong to 17 different parts of speech: NOUN (3846; 30% instances), PUNCT (1960; 15% instances), VERB (1199; 9% instances), AUX (1191; 9% instances), PRON (1144; 9% instances), ADV (855; 7% instances), PART (589; 5% instances), PROPN (523; 4% instances), SCONJ (408; 3% instances), CCONJ (391; 3% instances), ADP (239; 2% instances), ADJ (224; 2% instances), NUM (137; 1% instances), SYM (22; 0% instances), X (21; 0% instances), DET (9; 0% instances), INTJ (2; 0% instances)

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VERB in other languages: [am] [ar] [bg] [bxr] [ca] [ckb] [cop] [cs] [cu] [da] [de] [el] [en] [es] [et] [eu] [fa] [fi] [fo] [fr] [ga] [gl] [got] [grc] [he] [hi] [hr] [hu] [id] [it] [ja] [kk] [kmr] [ko] [la] [lv] [mr] [nl] [no] [pl] [pt] [ro] [ru] [sa] [sk] [sla] [sl] [so] [sr] [sv] [swl] [ta] [tr] [ug] [uk] [u] [urj] [ur] [vi] [yue] [zh]

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