Exam question 2 · Comeback stories: bald eagles, humpback whales, condors an…
State the measure principally responsible for the recovery of humpback whale populations.
Mova's choice: option 1 · The right answer: option 3 · wrong ✗ · Who acts: you, whale populations · What happens: state, recover · To what, where: measure
This is exam question 2 of lesson 282 «Comeback stories: bald eagles, humpback whales, condors and the kakapo» of the biology course of Mova's primary school, asked in stiff, formal language. The page gives the question's syntax tree — a dependency tree in the style of Universal Dependencies — and its pragmatics clause by clause, then the 4 options as the student saw them, each with its tree and pragmatics. Every text is parsed by Mova itself. How the student answered it, with the score of every option and why: the test at school.
The question
The words, one row each (CoNLL-U)
| # | word | lemma | UPOS | features | head | relation |
|---|---|---|---|---|---|---|
| 1 | State | state | VERB | Mood=Imp VerbForm=Fin | root | root |
| 2 | the | the | DET | Definite=Def PronType=Art | 3 measure | det |
| 3 | measure | measure | NOUN | Number=Sing | 1 State | obj |
| 4 | principally | principally | ADV | _ | 5 responsible | advmod |
| 5 | responsible | responsible | ADJ | Degree=Pos | 3 measure | amod |
| 6 | for | for | ADP | _ | 8 recovery | case |
| 7 | the | the | DET | Definite=Def PronType=Art | 8 recovery | det |
| 8 | recovery | recovery | NOUN | Number=Sing | 5 responsible | obl |
| 9 | of | of | ADP | _ | 12 populations | case |
| 10 | humpback | humpback | NOUN | Number=Sing | 11 whale | compound |
| 11 | whale | whale | NOUN | Number=Sing | 12 populations | compound |
| 12 | populations | population | NOUN | Number=Plur | 8 recovery | nmod |
| 13 | . | . | PUNCT | _ | 1 State | punct |
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
|---|---|---|---|---|---|---|---|---|---|
| 1 | state speech: other | imperative | you not said here | the measure | vn say-37.7-1-1 «NP V NP.topic»: agent=Agent measure=Topic | ||||
| 2 | recover | whale populations | nom recovery «event intransitive»: of=agent |
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.
The options
Option 1 · ← Mova's choice
The construction of artificial lakes
The words, one row each (CoNLL-U)
| # | word | lemma | UPOS | features | head | relation |
|---|---|---|---|---|---|---|
| 1 | The | the | DET | Definite=Def PronType=Art | 2 construction | det |
| 2 | construction | construction | NOUN | Number=Sing | root | root |
| 3 | of | of | ADP | _ | 5 lakes | case |
| 4 | artificial | artificial | ADJ | Degree=Pos | 5 lakes | amod |
| 5 | lakes | lake | NOUN | Number=Plur | 2 construction | nmod |
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
|---|---|---|---|---|---|---|---|---|---|
| 1 | construct | artificial lakes | nom construction «act transitive»: of=patient |
Option 2
The feeding of whales by fishing vessels
The words, one row each (CoNLL-U)
| # | word | lemma | UPOS | features | head | relation |
|---|---|---|---|---|---|---|
| 1 | The | the | DET | Definite=Def PronType=Art | 2 feeding | det |
| 2 | feeding | feeding | NOUN | Number=Sing | root | root |
| 3 | of | of | ADP | _ | 4 whales | case |
| 4 | whales | whale | NOUN | Number=Plur | 2 feeding | nmod |
| 5 | by | by | SCONJ | _ | 6 fishing | mark |
| 6 | fishing | fish | VERB | VerbForm=Ger | 2 feeding | acl |
| 7 | vessels | vessel | NOUN | Number=Plur | 6 fishing | obj |
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
|---|---|---|---|---|---|---|---|---|---|
| 1 | fish | gerund | the feeding of whales not said here | vessels | vn hunt-35.1 «NP V NP»: agent=Agent vessel=Theme | ||||
| 2 | feed | whales | nom feeding «act intransitive»: of=agent |
Option 3 · ✓ the right answer
The prohibition of commercial whaling in 1986
The words, one row each (CoNLL-U)
| # | word | lemma | UPOS | features | head | relation |
|---|---|---|---|---|---|---|
| 1 | The | the | DET | Definite=Def PronType=Art | 2 prohibition | det |
| 2 | prohibition | prohibition | NOUN | Number=Sing | root | root |
| 3 | of | of | ADP | _ | 5 whaling | case |
| 4 | commercial | commercial | ADJ | Degree=Pos | 5 whaling | amod |
| 5 | whaling | whaling | NOUN | Number=Sing | 2 prohibition | nmod |
| 6 | in | in | ADP | _ | 7 1986 | case |
| 7 | 1986 | 1986 | NUM | NumForm=Digit NumType=Card | 2 prohibition | nmod |
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
|---|---|---|---|---|---|---|---|---|---|
| 1 | prohibit | commercial whaling | nom prohibition «communication transitive»: of=patient |
Option 4
The removal of all sharks from the oceans
The words, one row each (CoNLL-U)
| # | word | lemma | UPOS | features | head | relation |
|---|---|---|---|---|---|---|
| 1 | The | the | DET | Definite=Def PronType=Art | 2 removal | det |
| 2 | removal | removal | NOUN | Number=Sing | root | root |
| 3 | of | of | ADP | _ | 5 sharks | case |
| 4 | all | all | DET | PronType=Tot | 5 sharks | det |
| 5 | sharks | shark | NOUN | Number=Plur | 2 removal | nmod |
| 6 | from | from | ADP | _ | 8 oceans | case |
| 7 | the | the | DET | Definite=Def PronType=Art | 8 oceans | det |
| 8 | oceans | ocean | NOUN | Number=Plur | 5 sharks | nmod |
| # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by |
|---|---|---|---|---|---|---|---|---|---|
| 1 | remove | all sharks from the oceans | nom removal «act transitive»: of=patient |
Text: the tests of Mova's primary school, written for Mova (world/data/school/), as the course runner gave them to the student. Trees: Mova's own parse — the en model on the CPU, when the site is built — not checked by a teacher; they may be wrong. Frames: Mova's frames reader (prag), each text read on its own. Elamur Cosmic License.
This page in Markdown → https://md.mova.elamur.ai/free/en/corpora/questions/biology/282-comeback-stories-bald-eagles-humpback-whales-condors-and-the-kakapo/e2/