Counting the AI in one ordinary day, sentence 9
Weather forecasts use computer models and AI to make good guesses, but weather is hard to predict, so forecasts are not promises.
Who acts: Weather forecasts, weather, forecasts · What happens: use, make, be, predict, not be · To what, where: computer models, good guesses, promises
This is a sentence of the lesson «Counting the AI in one ordinary day» 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 (Weather forecasts, weather, forecasts), what happens, when and where, as Mova's frames read it from the tree.
The tree
The words, one row each (CoNLL-U)
| # | word | lemma | UPOS | features | head | relation |
|---|---|---|---|---|---|---|
| 1 | Weather | weather | NOUN | Number=Sing | 2 forecasts | compound |
| 2 | forecasts | forecast | NOUN | Number=Plur | 3 use | nsubj |
| 3 | use | use | VERB | Mood=Ind Number=Plur Person=3 Tense=Pres VerbForm=Fin | root | root |
| 4 | computer | computer | NOUN | Number=Sing | 5 models | compound |
| 5 | models | model | NOUN | Number=Plur | 3 use | obj |
| 6 | and | and | CCONJ | _ | 7 AI | cc |
| 7 | AI | ai | NOUN | Number=Sing | 5 models | conj |
| 8 | to | to | PART | _ | 9 make | mark |
| 9 | make | make | VERB | VerbForm=Inf | 3 use | advcl |
| 10 | good | good | ADJ | Degree=Pos | 11 guesses | amod |
| 11 | guesses | guess | NOUN | Number=Plur | 9 make | obj |
| 12 | , | , | PUNCT | _ | 16 hard | punct |
| 13 | but | but | CCONJ | _ | 16 hard | cc |
| 14 | weather | weather | NOUN | Number=Sing | 16 hard | nsubj |
| 15 | is | be | AUX | Mood=Ind Number=Sing Person=3 Tense=Pres VerbForm=Fin | 16 hard | cop |
| 16 | hard | hard | ADJ | Degree=Pos | 3 use | conj |
| 17 | to | to | PART | _ | 18 predict | mark |
| 18 | predict | predict | VERB | VerbForm=Inf | 16 hard | ccomp |
| 19 | , | , | PUNCT | _ | 24 promises | punct |
| 20 | so | so | ADV | _ | 24 promises | advmod |
| 21 | forecasts | forecast | NOUN | Number=Plur | 24 promises | nsubj |
| 22 | are | be | AUX | Mood=Ind Number=Plur Person=3 Tense=Pres VerbForm=Fin | 24 promises | cop |
| 23 | not | not | PART | Polarity=Neg | 24 promises | advmod |
| 24 | promises | promise | NOUN | Number=Plur | 3 use | conj |
| 25 | . | . | PUNCT | _ | 3 use | punct |
Pragmatics
No stored speech act for this sentence.
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
|---|---|---|---|---|---|---|---|---|---|
| 1 | use | present | Weather forecasts | computer models and AI | vn eat-39.1 «NP V NP»: agent=Agent model=Patient | ||||
| 2 | make | to-infinitive | Weather forecasts not said here | good guesses | vn build-26.1-1 «NP.asset V NP»: agent=Asset guess=Product | ||||
| 3 | is | present | weather | hard property | tree rules | ||||
| 4 | predict | to-infinitive | weather not said here | vn indicate-78 «NP V how S»: agent=Pivot | |||||
| 5 | not is a | present | forecasts | promises | tree rules |
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:019-ai-in-one-ordinary-day.lesson:9.
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): R7-rel-agree ×2. 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/19-ai-in-one-ordinary-day/9/