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Difficulties in machine translation

machine translation

Ambiguities in the source language

  • Lexical ambiguities: polysemy. In The Challenge of Languages, Claude Piron said that May 4, 1991 he asked a machine to translate in French: In such a case, you can make a very good case for wooden case, a phrase he had just read and condensed. After a moment came the answer: “Dans un tel cas vous pouvez faire un très bon cas pour des cas inexpressifs.
  • Grammatical ambiguities: the same word can be of two different grammatical categories. Also in The Challenge of Languages the author offered to a machine, set interactively, He was sorting out food rations and chewing gum, phrase that can mean either “he was sorting rations and chewing gum” or “he was sorting rations while chewing gum. ” Instead of asking a question about the grammatical value of –ing in chewing, so instead of “interact”, the machine gave the following sentence: “Il triait dehors rations de nourriture et mastiquant la gencive.
  • Semantic ambiguities: the same word can have different meanings in different contexts.
  • Ambiguity of reference of pronouns.

To remove these ambiguities, the translator (human or automatic) must:

  • have, in addition to language skills, factual knowledge about the state of the world (for example, you must know if the person is female);
  • be able to perform a certain interpretation of the text submitted to you: if you meet “secretary”, you need to know, according to the target language, the sex of the secretary. It is easy to solve this problem in the case of a simple sentence like “John Doe’s secretary”: a simple rule can express the fact that the term “X’s Y” implies that Y “belongs” to X. If the program meets the phrase “I went to the accounting department and I talked to the secretary,” it is more difficult for the machine to make the relationship between secretaries and service that was just mentioned; the task is even more difficult in a context like “I saw Mr. John Doe, who gave me a document; I went to the accounting department to make a photocopy and I came back to give it to the secretary”: here you can not even rely on the proximity of the “secretary” and the name of service, since in fact is about the secretary of John Doe mentioned before in the sentence.

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