--- title: It learned by playing a giant game of "guess the missing word" over… — How a language model learns: guessing the next w… · tree and pragmatics description: It learned by playing a giant game of "guess the missing word" over and over with more text than you could read in thousands of lifetimes. Who acts: chatbot, giant game, you. A sentence of the lesson «How a language model learns: guessing the next word» of the ai course of Mova's primary school with --- [Mova](https://md.mova.elamur.ai/free/en/) · [this page in HTML](https://mova.elamur.ai/free/en/corpora/school/ai/2-guessing-the-next-word/1/) [home](https://md.mova.elamur.ai/free/en/) / [corpora](https://md.mova.elamur.ai/free/en/corpora/) / [school](https://md.mova.elamur.ai/free/en/corpora/school/) / [AI](https://md.mova.elamur.ai/free/en/corpora/school/ai/) / [How a language model learns: guessing…](https://md.mova.elamur.ai/free/en/corpora/school/ai/2-guessing-the-next-word/) / 1 # How a language model learns: guessing the next word, sentence 1 It learned by playing a giant game of "guess the missing word" over and over with more text than you could read in thousands of lifetimes. **Who acts:** chatbot, giant game, you · **What happens:** learn, play, guess, read · **To what, where:** giant game, missing word, more text, thousands 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 (chatbot, giant game, you), what happens, when and where, as Mova's frames read it from the tree. ## The tree {#tree} ```conllu # sent_id = school:ai:002-guessing-the-next-word.lesson:1 # text = It learned by playing a giant game of "guess the missing word" over and over with more text than you could read in thousands of lifetimes. # source = school lesson (ours) # course = ai # lesson = 002-guessing-the-next-word.lesson # annotation = Mova annot: Rust (en) → Haiku 5.5 (medium, Batches API) patches; gates UD 2.18; agreed by treeagree rules (Stanza, Trankit, spaCy trf): R5-strong ×1, R6-punct-agree ×1, R7-rel-agree ×1 1 It it PRON PRP Case=Nom|Gender=Neut|Number=Sing|Person=3|PronType=Prs 2 nsubj _ _ 2 learned learn VERB VBD Mood=Ind|Tense=Past|VerbForm=Fin 0 root _ _ 3 by by SCONJ IN _ 4 mark _ _ 4 playing play VERB VBG Tense=Pres|VerbForm=Part 2 advcl _ _ 5 a a DET DT Definite=Ind|PronType=Art 7 det _ _ 6 giant giant ADJ JJ Degree=Pos 7 amod _ _ 7 game game NOUN NN Number=Sing 4 obj _ _ 8 of of SCONJ IN _ 10 mark _ _ 9 " " PUNCT `` _ 10 punct _ _ 10 guess guess VERB VB VerbForm=Inf 7 acl _ _ 11 the the DET DT Definite=Def|PronType=Art 13 det _ _ 12 missing missing ADJ JJ Degree=Pos 13 amod _ _ 13 word word NOUN NN Number=Sing 10 obj _ _ 14 " " PUNCT '' _ 10 punct _ Agree=R6-punct-agree|Haiku=13:punct 15 over over ADV RB _ 10 advmod _ Agree=R7-rel-agree|Haiku=10:ccomp 16 and and CCONJ CC _ 17 cc _ _ 17 over over ADV RB _ 15 conj _ _ 18 with with ADP IN _ 20 case _ _ 19 more more ADJ JJR Degree=Cmp 20 amod _ _ 20 text text NOUN NN Number=Sing 10 obl _ _ 21 than than SCONJ IN _ 24 mark _ _ 22 you you PRON PRP Case=Nom|Person=2|PronType=Prs 24 nsubj _ _ 23 could could AUX MD VerbForm=Fin 24 aux _ _ 24 read read VERB VB VerbForm=Inf 20 acl _ Agree=R5-strong|Haiku=10:ccomp 25 in in ADP IN _ 26 case _ _ 26 thousands thousand NOUN NNS Number=Plur 24 obl _ _ 27 of of ADP IN _ 28 case _ _ 28 lifetimes lifetime NOUN NNS Number=Plur 26 nmod _ _ 29 . . PUNCT . _ 2 punct _ _ ``` ## Pragmatics {#pragmatics} No stored speech act for this sentence. | # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1 | **learn** | past | chatbot | | | | | | vn learn-14-1 «NP V»: agent=Agent | | 2 | **play** | gerund | chatbot *not said here* | a giant game | | | | | vn use-105.1 «NP V NP»: agent=Agent game=Theme | | 3 | **guess** *in a quote* | infinitive | a giant game *not said here* | the missing word | | | | with more text; over *property* | vn conjecture-29.5-1 «NP V NP»: agent=Agent word=Theme | | 4 | **read** | could | you | more text *not said here* | | thousands of lifetimes | | | vn transfer\_mesg-37.1.1-1 «NP V NP»: agent=Agent text=Topic | 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](https://creativecommons.org/licenses/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:1`. **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): R5-strong ×1, R6-punct-agree ×1, R7-rel-agree ×1. **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](https://md.mova.elamur.ai/free/en/releases/0.4/). - ← previous: [How a language model learns: guessing…, 0](https://md.mova.elamur.ai/free/en/corpora/school/ai/2-guessing-the-next-word/0/) - next →: [How a language model learns: guessing…, 2](https://md.mova.elamur.ai/free/en/corpora/school/ai/2-guessing-the-next-word/2/) - ↑ back to [the lesson](https://md.mova.elamur.ai/free/en/corpora/school/ai/2-guessing-the-next-word/)