--- title: Aarav: "Scholars in Toledo translating books? Like Google Translate,… — Ideas on the move: numbers, paper, let… · tree and pragmatics description: Aarav: "Scholars in Toledo translating books? Like Google Translate, but slow?" What did they actually do? Test 11 · ★ of lesson 75 «Ideas on the move: numbers, paper, letters, chess and news» of the history course of Mova's primary school, with the dependency tree and pragmatics of the question and --- [Mova](https://md.mova.elamur.ai/free/en/) · [this page in HTML](https://mova.elamur.ai/free/en/corpora/questions/history/75-ideas-on-the-move-numbers-paper-letters-chess-and-news/t11/) [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/) / [History](https://md.mova.elamur.ai/free/en/corpora/questions/history/) / [Ideas on the move: numbers, paper, let…](https://md.mova.elamur.ai/free/en/corpora/questions/history/75-ideas-on-the-move-numbers-paper-letters-chess-and-news/) / t11 # Test 11 · ★ · Ideas on the move: numbers, paper, letters, chess and news Aarav: "Scholars in Toledo translating books? Like Google Translate, but slow?" What did they actually do? **Mova's choice:** option 1 · **The right answer:** option 1 · right ✓ · **Who acts:** Scholars, books · **What happens:** translate, do · **To what, where:** books This is test 11 · ★ of lesson 75 «Ideas on the move: numbers, paper, letters, chess and news» of the history 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/history/75-ideas-on-the-move-numbers-paper-letters-chess-and-news/#t11). ## The question {#question} *Sentence 1:* Aarav: "Scholars in Toledo translating books? ```conllu # sent_id = question:history:75-ideas-on-the-move-numbers-paper-letters-chess-and-news:t11:1 # text = Aarav: "Scholars in Toledo translating books? 1 Aarav Aarav PROPN NNP Number=Sing 0 root _ SpaceAfter=No 2 : : PUNCT : _ 4 punct _ _ 3 " " PUNCT `` _ 4 punct _ SpaceAfter=No 4 Scholars scholar NOUN NNS Number=Plur 1 appos _ _ 5 in in ADP IN _ 6 case _ _ 6 Toledo Toledo PROPN NNP Number=Sing 4 nmod _ _ 7 translating translate VERB VBG VerbForm=Ger 4 acl _ _ 8 books book NOUN NNS Number=Plur 7 obj _ SpaceAfter=No 9 ? ? PUNCT . _ 1 punct _ _ ``` | # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1 | **translate** *in a quote* | gerund | Scholars in Toledo *not said here* | books | | | | | vn turn-26.6.1 «NP V NP»: agent=Agent book=Patient | 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:* Like Google Translate, but slow?" ```conllu # sent_id = question:history:75-ideas-on-the-move-numbers-paper-letters-chess-and-news:t11:2 # text = Like Google Translate, but slow?" 1 Like like ADP IN _ 3 case _ _ 2 Google Google PROPN NNP Number=Sing 3 compound _ _ 3 Translate Translate PROPN NNP Number=Sing 6 obl _ SpaceAfter=No 4 , , PUNCT , _ 6 punct _ _ 5 but but CCONJ CC _ 6 cc _ _ 6 slow slow ADJ JJ Degree=Pos 0 root _ SpaceAfter=No 7 ? ? PUNCT . _ 6 punct _ SpaceAfter=No 8 " " PUNCT '' _ 6 punct _ _ ``` The frames reader finds no event or fact in this sentence. *Sentence 3:* What did they actually do? ```conllu # sent_id = question:history:75-ideas-on-the-move-numbers-paper-letters-chess-and-news:t11:3 # text = What did they actually do? 1 What what PRON WP PronType=Int 2 nsubj _ _ 2 did do VERB VBD Mood=Ind|Number=Sing|Person=3|Tense=Past|VerbForm=Fin 0 root _ _ 3 they they PRON PRP Case=Nom|Number=Plur|Person=3|PronType=Prs 5 nsubj _ _ 4 actually actually ADV RB _ 5 advmod _ _ 5 do do VERB VBP Mood=Ind|Number=Plur|Person=3|Tense=Pres|VerbForm=Fin 2 ccomp _ SpaceAfter=No 6 ? ? PUNCT . _ 2 punct _ _ ``` | # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1 | **do** | past | | | | | | | tree rules | | 2 | **do** | present | books *= book* | | | | | actually *property* | vn act-114-1 «NP V»: agent=Agent | ## The options {#options} ### Option 1 · ← Mova's choice · ✓ the right answer {#o1} Translated Arabic books into Latin, bringing science to Europe ```conllu # sent_id = question:history:75-ideas-on-the-move-numbers-paper-letters-chess-and-news:t11:o1:1 # text = Translated Arabic books into Latin, bringing science to Europe 1 Translated translate VERB VBD Mood=Ind|Number=Sing|Person=1|Tense=Past|VerbForm=Fin 0 root _ _ 2 Arabic Arabic PROPN NNP Number=Sing 3 compound _ _ 3 books book NOUN NNS Number=Plur 1 obj _ _ 4 into into ADP IN _ 5 case _ _ 5 Latin Latin PROPN NNP Number=Sing 1 obl _ SpaceAfter=No 6 , , PUNCT , _ 7 punct _ _ 7 bringing bring VERB VBG Tense=Pres|VerbForm=Part 1 advcl _ _ 8 science science NOUN NN Number=Sing 7 obj _ _ 9 to to ADP IN _ 10 case _ _ 10 Europe Europe PROPN NNP Number=Sing 7 obl _ _ ``` | # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1 | **translate** | past | | Arabic books | | | | into Latin *result* | vn turn-26.6.1 «NP V NP.patient PP.result»: agent=Agent book=Patient into latin=Result | | 2 | **bring** | gerund | | science | Europe | | | | vn bring-11.3-1 «NP V NP PP.destination»: agent=Agent science=Theme to europe=Destination | ### Option 2 {#o2} Translated English books into Chinese ```conllu # sent_id = question:history:75-ideas-on-the-move-numbers-paper-letters-chess-and-news:t11:o2:1 # text = Translated English books into Chinese 1 Translated translate VERB VBD Mood=Ind|Number=Sing|Person=1|Tense=Past|VerbForm=Fin 0 root _ _ 2 English English PROPN NNP Number=Sing 3 compound _ _ 3 books book NOUN NNS Number=Plur 1 obj _ _ 4 into into ADP IN _ 5 case _ _ 5 Chinese Chinese ADJ JJ Degree=Pos 1 obl _ _ ``` | # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1 | **translate** | past | | English books | | | | into Chinese *result* | vn turn-26.6.1 «NP V NP.patient PP.result»: agent=Agent book=Patient into chinese=Result | ### Option 3 {#o3} Burned all foreign books ```conllu # sent_id = question:history:75-ideas-on-the-move-numbers-paper-letters-chess-and-news:t11:o3:1 # text = Burned all foreign books 1 Burned burn VERB VBN Tense=Past|VerbForm=Part|Voice=Pass 0 root _ _ 2 all all DET DT PronType=Tot 4 det _ _ 3 foreign foreign ADJ JJ Degree=Pos 4 amod _ _ 4 books book NOUN NNS Number=Plur 1 obj _ _ ``` | # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1 | **burn** | participle | | all foreign books | | | | | vn light\_emission-43.1 «NP V NP.theme»: agent=Agent book=Theme | ### Option 4 {#o4} Built the first computer ```conllu # sent_id = question:history:75-ideas-on-the-move-numbers-paper-letters-chess-and-news:t11:o4:1 # text = Built the first computer 1 Built build VERB VBD Mood=Ind|Number=Sing|Person=1|Tense=Past|VerbForm=Fin 0 root _ _ 2 the the DET DT Definite=Def|PronType=Art 4 det _ _ 3 first first ADJ JJ Degree=Pos|NumForm=Word|NumType=Ord 4 amod _ _ 4 computer computer NOUN NN Number=Sing 1 obj _ _ ``` | # | verb | tense, mood | who | what, whom | to whom | where | when | other | roles by | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1 | **build** | past | | the first computer | | | | | vn build-26.1-1 «NP.asset V NP»: agent=Asset computer=Product | **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: [Ideas on the move: numbers, paper, let…, test 10](https://md.mova.elamur.ai/free/en/corpora/questions/history/75-ideas-on-the-move-numbers-paper-letters-chess-and-news/t10/) - next →: [Ideas on the move: numbers, paper, let…, test 12](https://md.mova.elamur.ai/free/en/corpora/questions/history/75-ideas-on-the-move-numbers-paper-letters-chess-and-news/t12/) - ↑ back to [Ideas on the move: numbers, paper, letters, chess and news](https://md.mova.elamur.ai/free/en/corpora/questions/history/75-ideas-on-the-move-numbers-paper-letters-chess-and-news/)