Difference between revisions of "Biak/Transducer"
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==Code== | ==Code== | ||
Our github repository can be found here: [https://github.swarthmore.edu/Ling073-sp21/ling073-bhw Our Github] | Our github repository can be found here: [https://github.swarthmore.edu/Ling073-sp21/ling073-bhw Our Github] | ||
| − | ==Evaluation== | + | |
| + | ==Analyser Evaluation== | ||
*As of now, our Transducer passes 76/76 tests generated from our Wikipedia page. | *As of now, our Transducer passes 76/76 tests generated from our Wikipedia page. | ||
*Our initial transducer was capable of analyzing approximately 20% of our corpus file. | *Our initial transducer was capable of analyzing approximately 20% of our corpus file. | ||
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* We pass 76 tests of bhw.yaml | * We pass 76 tests of bhw.yaml | ||
* We pass 6 tests of commonwords.yaml | * We pass 6 tests of commonwords.yaml | ||
| + | |||
| + | ==Generator Evaluation== | ||
| + | *On our initial run of the generation tests, 107 tests were generated, of which we passed 75 and failed 32 | ||
| + | |||
[[Category:Sp21_Transducers]] | [[Category:Sp21_Transducers]] | ||
Revision as of 14:10, 17 March 2021
Code
Our github repository can be found here: Our Github
Analyser Evaluation
- As of now, our Transducer passes 76/76 tests generated from our Wikipedia page.
- Our initial transducer was capable of analyzing approximately 20% of our corpus file.
- Additions following initial analysis
- Added common conjunctions, allowing our transducer to cover 21.86%, then 22.6% of our original corpus.
- Added common adverbs and the noun for village, which brought coverage to 23.1%
- Added verb for "to say," which improved coverage to 23.9%
| Form | Meaning |
|---|---|
| ido<cnjsub> ↔ ido | when |
| inja<cnjcoo> ↔ inja | so |
| mnu<n> ↔ mnu | village |
| wer<adv> ↔ wer | again |
| kwar<adv> ↔ kwar | already |
| kaku<adv> ↔ kaku | very |
| obe<v><tv><p3><sg> ↔ dobe | say |
- Our transducer has 69 stems.
- Current coverage: 23.9%, 2,985 words.
- We pass 76 tests of bhw.yaml
- We pass 6 tests of commonwords.yaml
Generator Evaluation
- On our initial run of the generation tests, 107 tests were generated, of which we passed 75 and failed 32
