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How a language model learns: guessing the next word, sentence 6

"Large language model" means a huge program that has learned the patterns of how words are used.

Who acts: Large language model, huge program · What happens: mean, learn, use · To what, where: huge program, patterns, words

This is a sentence of the lesson «How a language model learns: guessing the next word» of the ai course of Mova's primary school. The page gives its syntax tree — a dependency tree in the style of Universal Dependencies — and its pragmatics clause by clause: who acts (Large language model, huge program), what happens, when and where, as Mova's frames read it from the tree.

The tree

punctamodcompoundnsubjpunctdetamodobjnsubjauxacl:relcldetobjmarkadvmodnsubj:passaux:passaclpunctroot"PUNCTLargeADJlanguageNOUNmodelNOUN"PUNCTmeansVERBaDEThugeADJprogramNOUNthatPRONhasAUXlearnedVERBtheDETpatternsNOUNofSCONJhowADVwordsNOUNareAUXusedVERB.PUNCT
The words, one row each (CoNLL-U)
#wordlemmaUPOSfeaturesheadrelation
1""PUNCT_4 modelpunct
2LargelargeADJDegree=Pos4 modelamod
3languagelanguageNOUNNumber=Sing4 modelcompound
4modelmodelNOUNNumber=Sing6 meansnsubj
5""PUNCT_4 modelpunct
6meansmeanVERBMood=Ind Number=Sing Person=3 Tense=Pres VerbForm=Finrootroot
7aaDETDefinite=Ind PronType=Art9 programdet
8hugehugeADJDegree=Pos9 programamod
9programprogramNOUNNumber=Sing6 meansobj
10thatthatPRONPronType=Rel12 learnednsubj
11hashaveAUXMood=Ind Number=Sing Person=3 Tense=Pres VerbForm=Fin12 learnedaux
12learnedlearnVERBTense=Past VerbForm=Part9 programacl:relcl
13thetheDETDefinite=Def PronType=Art14 patternsdet
14patternspatternNOUNNumber=Plur12 learnedobj
15ofofSCONJ_19 usedmark
16howhowADVPronType=Int19 usedadvmod
17wordswordNOUNNumber=Plur19 usednsubj:pass
18arebeAUXMood=Ind Number=Plur Person=3 Tense=Pres VerbForm=Fin19 usedaux:pass
19useduseVERBTense=Past VerbForm=Part Voice=Pass14 patternsacl
20..PUNCT_6 meanspunct

Pragmatics

form
statement
act
assert
voice
narrator
polarity
none
teacher
kept the draft
#verbtense, moodwhowhat, whomto whomwherewhenotherroles by
1meanpresentLarge language modela huge programvn intend-61.2-1 «NP V NP»: agent=Agent program=Topic
2learnpresent · perfecta huge programthe patternsvn learn-14-2-1 «NP V NP»: agent=Agent pattern=Topic
3usepresent · passivewordsvn eat-39.1 «NP V NP»: subject=Patient

One row per clause the reader finds. «not said here»: a role filled from the clause above. «roles by»: a VerbNet class and frame when one fits the verb, else the reader's rules on the tree.

Licence: CC BY-SA 4.0, as the whole of Mova corpus 0.4, of which this treebank (the agreed school, mova-school-agreed-en.conllu) is part. The lessons were written for Mova's primary school. Sentence school:ai:002-guessing-the-next-word.lesson:6.

The tree: Mova annot: Rust (en) → Haiku 5.5 (medium, Batches API) patches; gates UD 2.18; agreed by treeagree rules (Stanza, Trankit, spaCy trf): no change. The frames are read from the tree by Mova's frames reader (prag) when this page is built, the lesson read in order, so a pronoun may be resolved from an earlier sentence.

See the release 0.4.

This page in Markdown → https://md.mova.elamur.ai/free/en/corpora/school/ai/2-guessing-the-next-word/6/