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Recent Posts
- Grammatical taxonomy again: the case of prepositions
- Creating new grammatical types
- Evaluation of the performance after changes
- Evaluating the performance of the translation after the changes made
- Grammatical word-disambiguation again and again
- First feasability test: dictionary morphing
- Translation from Italian to Gallurese
- Adjective modifiers again
- On ‘reflexive pronouns’
- Grammatical word-disambiguation again
- First steps in gallurese language
- Hinting at the Control problem
- On the implementation of grammatical disambiguation
- The 90% rule
- A “traducidori gaddhuresu” in preparation
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Tags
- adjective accordance
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Monthly Archives: January 2018
Proper nouns: handling some false positives
Now handling some kind of false positives related to proper nouns translation. As this type of error is somewhat widespread, it could result in a 0.2% increase in overall accuracy. Of interest in the present case: recall that ‘détroit’ is … Continue reading
Testing self-evaluation accuracy
Testing self-evaluation accuracy: in the present case, it yields a 100% performance. However, there is one error ‘par des explosifs’ should read da splusivi or even da i splusivi (by explosives): a problem of partitive article. Arguably, there is a second … Continue reading
Adjective disambiguation: a hard case
A hard case of disambiguation is successfully handled here (amid some vocabulary errors) : ‘les premiers parachutistes des 82e et 101e divisions…’ is properly translated into … di i 82a è 101a divisioni… It is a hard case, since ultima … Continue reading
Proper nouns: false positives again
Now we face false positives again: French proper noun ‘Détroit’ is translated erroneously into Strittonu when it shouls have been left untradslated, being a proper noun. The ambiguity of ‘Détroit’ lies in the fact that it can be translated either into: Détroit, … Continue reading
Evaluation of machine translation: why not self-evaluation?
Evaluation of machine translation is usually done via external tools (to cite some instances: ARPA, BLEU, METEOR, LEPOR, …). But let us investigate the idea of self-evaluation. For it seems that the software itself is capable of having an accurate … Continue reading
