Johanna MONTI, Anabela BARREIRO, Annibale ELIA, Federica MARANO, Antonella NAPOLI

Taking on new challenges in multi-word unit processing for machine

translation

Outline

2Taking on new challenges in Multi-word Unit processing for machine translation – FreeBMT 2011

Multi-word units in the Lexicon-Grammar: definition

3Taking on new challenges in Multi-word Unit processing for machine translation –

FreeBMT 2011

Multi-word units in the Lexicon-Grammar

4Taking on new challenges in Multi-word Unit processing for machine translation –

FreeBMT 2011

Multi-word units in the Lexicon-Grammar : part of a continuum

5Taking on new challenges in Multi-word Unit processing for machine translation –

FreeBMT 2011

Multi-word units in the Lexicon-Grammar: lemmatization

6Taking on new challenges in Multi-word Unit processing for machine translation –

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Multi-word units in the Lexicon-Grammar: lemmatization criteria

7Taking on new challenges in Multi-word Unit processing for machine translation –

FreeBMT 2011

The corpus-linguistic approach

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Multi-word units in Machine Translation

9Taking on new challenges in Multi-word Unit processing for machine translation –

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Multi-word units in Machine Translation: main problems

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Multi-word units in Machine Translation: different approaches

Taking on new challenges in Multi-word Unit processing for machine translation – FreeBMT 2011

Lexical ambiguities handled by different systems

• Corpus: non-specialized texts approx. 300 sentences (10,000 words) multi-word units extracted from the Web

Webcorp LSE, Web as a Corpus

• MT systems : Google TranslateOpenLogos

12Taking on new challenges in Multi-word Unit processing for machine translation –

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Typical ambiguities: examples

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Typical ambiguities: examples

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Integration of Semantico-Syntactic knowledge

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Integration of Semantico-Syntactic knowledge

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Integration of Semantico-Syntactic knowledge: mix up

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Semantic table (SEMTAB ) rule

Italian Transfer

MIX UP(VT) IN MESCOLARE IN

MIX UP(VT) N IN MESCOLARE N IN

MIX UP(VT) N WITH CONFONDERE N CON

MIX UP(VT) N(HUMAN) IN CONFONDERE N IN

MIX UP(VT) N(INGREDIENT) MESCOLARE N

MIX UP(VT) N(MEDICINE) PREPARARE N

MIX UP(VT) WITH CONFONDERE CON

MIX UP(VT) N(HUMAN,INFO) WITH CONFONDERE N CON

SemTab rules comment lines for the verb mix up

Taking on new challenges in Multi-word Unit processing for machine translation – FreeBMT 2011

Qualitative MT Evaluation metrics

19Taking on new challenges in Multi-word Unit processing for machine translation –

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Qualitative MT Evaluation metrics

20Taking on new challenges in Multi-word Unit processing for machine translation –

FreeBMT 2011

Qualitative MT Evaluation metrics

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Qualitative MT Evaluation metrics

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Qualitative MT Evaluation metrics: the «ideal» evaluation tool

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Conclusions

24Taking on new challenges in Multi-word Unit processing for machine translation –

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Johanna MONTI, Anabela BARREIROAnnibale ELIA, Federica MARANO, Antonella NAPOLI

Thank you for your attention !