By José Luis Vicedo, Particio Martínez-Barco, Rafael Munoz, Maximiliano Saiz Noeda
This publication constitutes the refereed court cases of the 4th foreign convention, EsTAL 2004, held in Alicante, Spain in October 2004.
The forty two revised complete papers provided have been rigorously reviewed and chosen from seventy two submissions. The papers handle present matters in computational linguistics and monolingual and multilingual clever language processing and purposes, specifically written language research and iteration; pragmatics, discourse, semantics, syntax, and morphology; lexical assets; be aware feel disambiguation; linguistic, mathematical, and morphology; lexical assets; notice experience disambiguation; linguistic, mathematical, and mental versions of language; wisdom acquisition and illustration; corpus-based and statistical language modeling; desktop translation and translation instruments; and computational lexicography; details retrieval; extraction and query answering; automated summarization; rfile categorization; normal language interfaces; and discussion platforms and evaluate of systems.
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Extra info for Advances in natural language processing: 4th international conference, EsTAL 2004, Alicante, Spain, October 20-22, 2004: proceedings
An additional attributive suffix DAKE (only) as in KATAMEN DAKE NI is transferred unchanged to be translated in a second step as shown in Example 3: Of course, also facts for predicate (5) can contain shared variables for unification to enable the acquisition of general transfer rules. Example 10. 3 Rules for Translating Conjunctions German (or English) conjunctions are expressed in Japanese mainly with the help of conjunctive particles. e. the phrase type. Therefore, we provide the following predicate for the definition of general transfer rules for situations where the argument A1 of a simple constituent is only translated to A2 if the constituent name of the complex constituent in which it is included equals CI: Example 11.
5 Representing Syntactic Dependences In order to extend the system with information about the syntactic dependences between the words in the texts, we have tried an extended version of the system in which the references and the candidate answer are analysed with a parser and next the dependences between the words are extracted. The library we have used for parsing is the wraetlic tools 2. Figure 3 shows the dependences obtained from the candidate text from Figure 2. This can be taken as a first step in obtaining a logical representation of the text, but there are currently some limitations of our parser which do not allow us to produce a more reliable semantic analysis: it does not currently support prepositional-phrase attachment or coreference resolution.
Automatic Acquisition of Transfer Rules from Translation Examples 23 Fig. 2. Example of rule acquisition The predicate tf_acc(A1, A2) is used for finding and applying transfer rules of type tr_acc; if no transfer rule can be applied, the constituent is left unchanged: The recursive call for translating a subconstituent Csub(Asub) is realized with the predicate tf_sub(Csub, A1, A2): and the predicate tf_sub_arg(Csub, Asub, A1, A2), which consists of several rules that either: find and apply a rule of type tr_sc: tf_sub_arg(Csub, Asub, A1, A2): tr_sc(Csub, Csub2, Asub, Asub2), repl_diff(Csub, Csub2, A1, Asub2, A2).