--- title: Count them: a tea picker picks from 4 shoots, taking two leaves and… — Sugar, chocolate, tea and coffee: the… · tree and pragmatics description: Count them: a tea picker picks from 4 shoots, taking two leaves and a bud from each. How many bits does she pick? Test 2 of lesson 347 «Sugar, chocolate, tea and coffee: the plants behind treats» of the biology course of Mova's primary school, with the dependency tree and pragmatics of the question --- [Mova](https://md.mova.elamur.ai/free/en/) · [this page in HTML](https://mova.elamur.ai/free/en/corpora/questions/biology/347-sugar-chocolate-tea-and-coffee-the-plants-behind-treats/t2/) [home](https://md.mova.elamur.ai/free/en/) / [corpora](https://md.mova.elamur.ai/free/en/corpora/) / [questions](https://md.mova.elamur.ai/free/en/corpora/questions/) / [Biology](https://md.mova.elamur.ai/free/en/corpora/questions/biology/) / [Sugar, chocolate, tea and coffee: the…](https://md.mova.elamur.ai/free/en/corpora/questions/biology/347-sugar-chocolate-tea-and-coffee-the-plants-behind-treats/) / t2 # Test 2 · Sugar, chocolate, tea and coffee: the plants behind treats Count them: a tea picker picks from 4 shoots, taking two leaves and a bud from each. How many bits does she pick? **Mova's choice:** option 1 · **The right answer:** option 2 · wrong ✗ · **Who acts:** you, tea picker, many bits · **What happens:** count, pick, take · **To what, where:** them, two leaves, each This is test 2 of lesson 347 «Sugar, chocolate, tea and coffee: the plants behind treats» of the biology course of Mova's primary school. 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](https://md.mova.elamur.ai/free/en/school-run/biology/347-sugar-chocolate-tea-and-coffee-the-plants-behind-treats/#t2). ## The question {#question} *Sentence 1:* Count them: a tea picker picks from 4 shoots, taking two leaves and a bud from each. ```conllu # sent_id = question:biology:347-sugar-chocolate-tea-and-coffee-the-plants-behind-treats:t2:1 # text = Count them: a tea picker picks from 4 shoots, taking two leaves and a bud from each. 1 Count count VERB VB Mood=Imp|VerbForm=Fin 0 root _ _ 2 them they PRON PRP Case=Acc|Number=Plur|Person=3|PronType=Prs 1 obj _ SpaceAfter=No 3 : : PUNCT : _ 7 punct _ _ 4 a a DET DT Definite=Ind|PronType=Art 6 det _ _ 5 tea tea NOUN NN Number=Sing 6 compound _ _ 6 picker picker NOUN NN Number=Sing 7 nsubj _ _ 7 picks pick VERB VBZ Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin 1 parataxis _ _ 8 from from ADP IN _ 10 case _ _ 9 4 4 NUM CD NumForm=Digit|NumType=Card 10 nummod _ _ 10 shoots shoot NOUN NNS Number=Plur 7 obl _ SpaceAfter=No 11 , , PUNCT , _ 12 punct _ _ 12 taking take VERB VBG Tense=Pres|VerbForm=Part 7 advcl _ _ 13 two two NUM CD NumForm=Word|NumType=Card 14 nummod _ _ 14 leaves leaf NOUN NNS Number=Plur 12 obj _ _ 15 and and CCONJ CC _ 17 cc _ _ 16 a a DET DT Definite=Ind|PronType=Art 17 det _ _ 17 bud bud NOUN NN Number=Sing 14 conj _ _ 18 from from ADP IN _ 19 case _ _ 19 each each DET DT PronType=Tot 12 obl _ SpaceAfter=No 20 . . PUNCT . _ 1 punct _ _ ``` | # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1 | **count** | imperative | you *not said here* | them *= they* | | | | | vn multiply-108 «NP V NP»: agent=Agent they=Theme | | 2 | **pick** | present | a tea picker | | | | | from 4 shoots | vn chew-39.2 «NP V PP»: agent=Agent from shoot=Patient | | 3 | **take** | gerund | a tea picker *not said here* | two leaves and a bud | | each | | | vn bring-11.3 «NP V NP PP.initial\_location»: agent=Agent leaf=Theme from each=Initial\_Location | 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. *Sentence 2:* How many bits does she pick? ```conllu # sent_id = question:biology:347-sugar-chocolate-tea-and-coffee-the-plants-behind-treats:t2:2 # text = How many bits does she pick? 1 How how ADV WRB PronType=Int 2 advmod _ _ 2 many many ADJ JJ Degree=Pos 3 amod _ _ 3 bits bit NOUN NNS Number=Plur 6 nsubj _ _ 4 does do AUX VBZ Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin 6 aux _ _ 5 she she PRON PRP Case=Nom|Gender=Fem|Number=Sing|Person=3|PronType=Prs 6 nsubj _ _ 6 pick pick VERB VB VerbForm=Inf 0 root _ SpaceAfter=No 7 ? ? PUNCT . _ 6 punct _ _ ``` | # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1 | **pick** | present · do-support | many bits | | | | | | vn chew-39.2 «NP V»: agent=Agent | ## The options {#options} ### Option 1 · ← Mova's choice {#o1} 8 ```conllu # sent_id = question:biology:347-sugar-chocolate-tea-and-coffee-the-plants-behind-treats:t2:o1:1 # text = 8 1 8 8 NUM CD NumForm=Digit|NumType=Card 0 root _ _ ``` The frames reader finds no event or fact in this sentence. ### Option 2 · ✓ the right answer {#o2} 12 ```conllu # sent_id = question:biology:347-sugar-chocolate-tea-and-coffee-the-plants-behind-treats:t2:o2:1 # text = 12 1 12 12 NUM CD NumForm=Digit|NumType=Card 0 root _ _ ``` The frames reader finds no event or fact in this sentence. ### Option 3 {#o3} 16 ```conllu # sent_id = question:biology:347-sugar-chocolate-tea-and-coffee-the-plants-behind-treats:t2:o3:1 # text = 16 1 16 16 NUM CD NumForm=Digit|NumType=Card 0 root _ _ ``` The frames reader finds no event or fact in this sentence. ### Option 4 {#o4} 4 ```conllu # sent_id = question:biology:347-sugar-chocolate-tea-and-coffee-the-plants-behind-treats:t2:o4:1 # text = 4 1 4 4 NUM CD NumForm=Digit|NumType=Card 0 root _ _ ``` The frames reader finds no event or fact in this sentence. **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. - ← previous: [Sugar, chocolate, tea and coffee: the…, test 1](https://md.mova.elamur.ai/free/en/corpora/questions/biology/347-sugar-chocolate-tea-and-coffee-the-plants-behind-treats/t1/) - next →: [Sugar, chocolate, tea and coffee: the…, test 3](https://md.mova.elamur.ai/free/en/corpora/questions/biology/347-sugar-chocolate-tea-and-coffee-the-plants-behind-treats/t3/) - ↑ back to [Sugar, chocolate, tea and coffee: the plants behind treats](https://md.mova.elamur.ai/free/en/corpora/questions/biology/347-sugar-chocolate-tea-and-coffee-the-plants-behind-treats/)