--- title: A simple next-word guesser counts which words came after a word in i… — Olympiad: thinking like a machine, Bebras puzzle… · tree and pragmatics description: A simple next-word guesser counts which words came after a word in its text and picks the one it saw most often. Who acts: simple word guesser, words, guesser. A sentence of the lesson «Olympiad: thinking like a machine, Bebras puzzles ★★★» of the ai course of Mova's primary school with its dependen --- [Mova](https://md.mova.elamur.ai/free/en/) · [this page in HTML](https://mova.elamur.ai/free/en/corpora/school/ai/31-olympiad-thinking-like-a-machine/7/) [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/) / [Olympiad: thinking like a machine, Beb…](https://md.mova.elamur.ai/free/en/corpora/school/ai/31-olympiad-thinking-like-a-machine/) / 7 # Olympiad: thinking like a machine, Bebras puzzles ★★★, sentence 7 A simple next-word guesser counts which words came after a word in its text and picks the one it saw most often. **Who acts:** simple word guesser, words, guesser · **What happens:** count, come, pick, see · **To what, where:** text, one This is a sentence of the lesson «Olympiad: thinking like a machine, Bebras puzzles ★★★» 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 (simple word guesser, words, guesser), what happens, when and where, as Mova's frames read it from the tree. ## The tree {#tree} ```conllu # sent_id = school:ai:031-olympiad-thinking-like-a-machine.lesson:7 # text = A simple next-word guesser counts which words came after a word in its text and picks the one it saw most often. # source = school lesson (ours) # course = ai # lesson = 031-olympiad-thinking-like-a-machine.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): R1-cc-next ×1, R6-punct-agree ×1 1 A a DET DT Definite=Ind|PronType=Art 6 det _ _ 2 simple simple ADJ JJ Degree=Pos 6 amod _ _ 3 next next ADJ JJ Degree=Pos 5 amod _ _ 4 - - PUNCT HYPH _ 5 punct _ _ 5 word word NOUN NN Number=Sing 6 compound _ _ 6 guesser guesser NOUN NN Number=Sing 7 nsubj _ _ 7 counts count VERB VBZ Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin 0 root _ _ 8 which which DET WDT PronType=Rel 9 det _ _ 9 words word NOUN NNS Number=Plur 10 nsubj _ _ 10 came come VERB VBD Mood=Ind|Number=Plur|Person=3|Tense=Past|VerbForm=Fin 7 ccomp _ _ 11 after after ADP IN _ 13 case _ _ 12 a a DET DT Definite=Ind|PronType=Art 13 det _ _ 13 word word NOUN NN Number=Sing 10 obl _ _ 14 in in ADP IN _ 16 case _ _ 15 its its PRON PRP$ Case=Gen|Gender=Neut|Number=Sing|Person=3|Poss=Yes|PronType=Prs 16 nmod:poss _ _ 16 text text NOUN NN Number=Sing 10 obl _ _ 17 and and CCONJ CC _ 18 cc _ Agree=R1-cc-next|Haiku=10:cc 18 picks pick VERB VBZ Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin 10 conj _ _ 19 the the DET DT Definite=Def|PronType=Art 20 det _ _ 20 one one NOUN NN Number=Sing 18 obj _ _ 21 it it PRON PRP Case=Nom|Gender=Neut|Number=Sing|Person=3|PronType=Prs 22 nsubj _ _ 22 saw see VERB VBD Mood=Ind|Number=Sing|Person=3|Tense=Past|VerbForm=Fin 20 acl:relcl _ _ 23 most most ADV RBS Degree=Sup 24 advmod _ _ 24 often often ADV RB _ 22 advmod _ _ 25 . . PUNCT . _ 7 punct _ Agree=R6-punct-agree|Haiku=5:punct ``` ## Pragmatics {#pragmatics} No stored speech act for this sentence. | # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1 | **count** | present | a simple word guesser | | | | | | vn characterize-29.2 «NP V NP to be ADJ»: agent=Agent clause=Attribute | | 2 | **come** | past | which words | | | word's text | after a word | | vn appear-48.1.1 «NP V PP.location»: agent=Theme in text=Location | | 3 | **pick** | present | which words *not said here* | the one | | | | | vn chew-39.2 «NP V NP»: agent=Agent one=Patient | | 4 | **see** | past | guesser | the one *not said here* | | | | often *property* | vn comprehend-87.2-1-1 «NP V NP»: agent=Experiencer one=Stimulus | 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:031-olympiad-thinking-like-a-machine.lesson:7`. **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): R1-cc-next ×1, R6-punct-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: [Olympiad: thinking like a machine, Beb…, 6](https://md.mova.elamur.ai/free/en/corpora/school/ai/31-olympiad-thinking-like-a-machine/6/) - next →: [Olympiad: thinking like a machine, Beb…, 8](https://md.mova.elamur.ai/free/en/corpora/school/ai/31-olympiad-thinking-like-a-machine/8/) - ↑ back to [the lesson](https://md.mova.elamur.ai/free/en/corpora/school/ai/31-olympiad-thinking-like-a-machine/)