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<p class="title is-5 mathjax"> More Victories, Less Cooperation: Assessing Cicero&#39;s Diplomacy Play </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Wongkamjan%2C+W">Wichayaporn Wongkamjan</a>, <a href="/search/cs?searchtype=author&amp;query=Gu%2C+F">Feng Gu</a>, <a href="/search/cs?searchtype=author&amp;query=Wang%2C+Y">Yanze Wang</a>, <a href="/search/cs?searchtype=author&amp;query=Hermjakob%2C+U">Ulf Hermjakob</a>, <a href="/search/cs?searchtype=author&amp;query=May%2C+J">Jonathan May</a>, <a href="/search/cs?searchtype=author&amp;query=Stewart%2C+B+M">Brandon M. Stewart</a>, <a href="/search/cs?searchtype=author&amp;query=Kummerfeld%2C+J+K">Jonathan K. Kummerfeld</a>, <a href="/search/cs?searchtype=author&amp;query=Peskoff%2C+D">Denis Peskoff</a>, <a href="/search/cs?searchtype=author&amp;query=Boyd-Graber%2C+J+L">Jordan Lee Boyd-Graber</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2406.04643v1-abstract-short" style="display: inline;"> The boardgame Diplomacy is a challenging setting for communicative and cooperative artificial intelligence. The most prominent communicative Diplomacy AI, Cicero, has excellent strategic abilities, exceeding human players. However, the best Diplomacy players master communication, not just tactics, which is why the game has received attention as an AI challenge. This work seeks to understand the de&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2406.04643v1-abstract-full').style.display = 'inline'; document.getElementById('2406.04643v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2406.04643v1-abstract-full" style="display: none;"> The boardgame Diplomacy is a challenging setting for communicative and cooperative artificial intelligence. The most prominent communicative Diplomacy AI, Cicero, has excellent strategic abilities, exceeding human players. However, the best Diplomacy players master communication, not just tactics, which is why the game has received attention as an AI challenge. This work seeks to understand the degree to which Cicero succeeds at communication. First, we annotate in-game communication with abstract meaning representation to separate in-game tactics from general language. Second, we run two dozen games with humans and Cicero, totaling over 200 human-player hours of competition. While AI can consistently outplay human players, AI-Human communication is still limited because of AI&#39;s difficulty with deception and persuasion. This shows that Cicero relies on strategy and has not yet reached the full promise of communicative and cooperative AI. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2406.04643v1-abstract-full').style.display = 'none'; document.getElementById('2406.04643v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 June, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2024. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2304.09919">arXiv:2304.09919</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2304.09919">pdf</a>, <a href="https://arxiv.org/format/2304.09919">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> </div> </div> <p class="title is-5 mathjax"> The eBible Corpus: Data and Model Benchmarks for Bible Translation for Low-Resource Languages </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Akerman%2C+V">Vesa Akerman</a>, <a href="/search/cs?searchtype=author&amp;query=Baines%2C+D">David Baines</a>, <a href="/search/cs?searchtype=author&amp;query=Daspit%2C+D">Damien Daspit</a>, <a href="/search/cs?searchtype=author&amp;query=Hermjakob%2C+U">Ulf Hermjakob</a>, <a href="/search/cs?searchtype=author&amp;query=Jang%2C+T">Taeho Jang</a>, <a href="/search/cs?searchtype=author&amp;query=Leong%2C+C">Colin Leong</a>, <a href="/search/cs?searchtype=author&amp;query=Martin%2C+M">Michael Martin</a>, <a href="/search/cs?searchtype=author&amp;query=Mathew%2C+J">Joel Mathew</a>, <a href="/search/cs?searchtype=author&amp;query=Robie%2C+J">Jonathan Robie</a>, <a href="/search/cs?searchtype=author&amp;query=Schwarting%2C+M">Marcus Schwarting</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2304.09919v1-abstract-short" style="display: inline;"> Efficiently and accurately translating a corpus into a low-resource language remains a challenge, regardless of the strategies employed, whether manual, automated, or a combination of the two. Many Christian organizations are dedicated to the task of translating the Holy Bible into languages that lack a modern translation. Bible translation (BT) work is currently underway for over 3000 extremely l&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2304.09919v1-abstract-full').style.display = 'inline'; document.getElementById('2304.09919v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2304.09919v1-abstract-full" style="display: none;"> Efficiently and accurately translating a corpus into a low-resource language remains a challenge, regardless of the strategies employed, whether manual, automated, or a combination of the two. Many Christian organizations are dedicated to the task of translating the Holy Bible into languages that lack a modern translation. Bible translation (BT) work is currently underway for over 3000 extremely low resource languages. We introduce the eBible corpus: a dataset containing 1009 translations of portions of the Bible with data in 833 different languages across 75 language families. In addition to a BT benchmarking dataset, we introduce model performance benchmarks built on the No Language Left Behind (NLLB) neural machine translation (NMT) models. Finally, we describe several problems specific to the domain of BT and consider how the established data and model benchmarks might be used for future translation efforts. For a BT task trained with NLLB, Austronesian and Trans-New Guinea language families achieve 35.1 and 31.6 BLEU scores respectively, which spurs future innovations for NMT for low-resource languages in Papua New Guinea. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2304.09919v1-abstract-full').style.display = 'none'; document.getElementById('2304.09919v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 19 April, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2302.00778">arXiv:2302.00778</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/2302.00778">pdf</a>, <a href="https://arxiv.org/format/2302.00778">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> </div> <p class="title is-5 mathjax"> User Study for Improving Tools for Bible Translation </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Mathew%2C+J">Joel Mathew</a>, <a href="/search/cs?searchtype=author&amp;query=Hermjakob%2C+U">Ulf Hermjakob</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2302.00778v1-abstract-short" style="display: inline;"> Technology has increasingly become an integral part of the Bible translation process. Over time, both the translation process and relevant technology have evolved greatly. More recently, the field of Natural Language Processing (NLP) has made great progress in solving some problems previously thought impenetrable. Through this study we endeavor to better understand and communicate about a segment&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2302.00778v1-abstract-full').style.display = 'inline'; document.getElementById('2302.00778v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2302.00778v1-abstract-full" style="display: none;"> Technology has increasingly become an integral part of the Bible translation process. Over time, both the translation process and relevant technology have evolved greatly. More recently, the field of Natural Language Processing (NLP) has made great progress in solving some problems previously thought impenetrable. Through this study we endeavor to better understand and communicate about a segment of the current landscape of the Bible translation process as it relates to technology and identify pertinent issues. We conduct several interviews with individuals working in different levels of the Bible translation process from multiple organizations to identify gaps and bottlenecks where technology (including recent advances in AI) could potentially play a pivotal role in reducing translation time and improving overall quality. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2302.00778v1-abstract-full').style.display = 'none'; document.getElementById('2302.00778v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 1 February, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">5 pages, Report of user-study</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1512.01587">arXiv:1512.01587</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/1512.01587">pdf</a>, <a href="https://arxiv.org/format/1512.01587">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Information Retrieval">cs.IR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> Extracting Biomolecular Interactions Using Semantic Parsing of Biomedical Text </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Garg%2C+S">Sahil Garg</a>, <a href="/search/cs?searchtype=author&amp;query=Galstyan%2C+A">Aram Galstyan</a>, <a href="/search/cs?searchtype=author&amp;query=Hermjakob%2C+U">Ulf Hermjakob</a>, <a href="/search/cs?searchtype=author&amp;query=Marcu%2C+D">Daniel Marcu</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1512.01587v1-abstract-short" style="display: inline;"> We advance the state of the art in biomolecular interaction extraction with three contributions: (i) We show that deep, Abstract Meaning Representations (AMR) significantly improve the accuracy of a biomolecular interaction extraction system when compared to a baseline that relies solely on surface- and syntax-based features; (ii) In contrast with previous approaches that infer relations on a sent&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1512.01587v1-abstract-full').style.display = 'inline'; document.getElementById('1512.01587v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1512.01587v1-abstract-full" style="display: none;"> We advance the state of the art in biomolecular interaction extraction with three contributions: (i) We show that deep, Abstract Meaning Representations (AMR) significantly improve the accuracy of a biomolecular interaction extraction system when compared to a baseline that relies solely on surface- and syntax-based features; (ii) In contrast with previous approaches that infer relations on a sentence-by-sentence basis, we expand our framework to enable consistent predictions over sets of sentences (documents); (iii) We further modify and expand a graph kernel learning framework to enable concurrent exploitation of automatically induced AMR (semantic) and dependency structure (syntactic) representations. Our experiments show that our approach yields interaction extraction systems that are more robust in environments where there is a significant mismatch between training and test conditions. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1512.01587v1-abstract-full').style.display = 'none'; document.getElementById('1512.01587v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 4 December, 2015; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> December 2015. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Appearing in Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16)</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1504.06665">arXiv:1504.06665</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/1504.06665">pdf</a>, <a href="https://arxiv.org/format/1504.06665">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> </div> </div> <p class="title is-5 mathjax"> Using Syntax-Based Machine Translation to Parse English into Abstract Meaning Representation </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Pust%2C+M">Michael Pust</a>, <a href="/search/cs?searchtype=author&amp;query=Hermjakob%2C+U">Ulf Hermjakob</a>, <a href="/search/cs?searchtype=author&amp;query=Knight%2C+K">Kevin Knight</a>, <a href="/search/cs?searchtype=author&amp;query=Marcu%2C+D">Daniel Marcu</a>, <a href="/search/cs?searchtype=author&amp;query=May%2C+J">Jonathan May</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1504.06665v2-abstract-short" style="display: inline;"> We present a parser for Abstract Meaning Representation (AMR). We treat English-to-AMR conversion within the framework of string-to-tree, syntax-based machine translation (SBMT). To make this work, we transform the AMR structure into a form suitable for the mechanics of SBMT and useful for modeling. We introduce an AMR-specific language model and add data and features drawn from semantic resources&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1504.06665v2-abstract-full').style.display = 'inline'; document.getElementById('1504.06665v2-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1504.06665v2-abstract-full" style="display: none;"> We present a parser for Abstract Meaning Representation (AMR). We treat English-to-AMR conversion within the framework of string-to-tree, syntax-based machine translation (SBMT). To make this work, we transform the AMR structure into a form suitable for the mechanics of SBMT and useful for modeling. We introduce an AMR-specific language model and add data and features drawn from semantic resources. Our resulting AMR parser improves upon state-of-the-art results by 7 Smatch points. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1504.06665v2-abstract-full').style.display = 'none'; document.getElementById('1504.06665v2-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 28 April, 2015; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 24 April, 2015; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2015. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">10 pages, 8 figures</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">ACM Class:</span> I.2.7 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/cmp-lg/9706029">arXiv:cmp-lg/9706029</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/cmp-lg/9706029">pdf</a>, <a href="https://arxiv.org/ps/cmp-lg/9706029">ps</a>, <a href="https://arxiv.org/format/cmp-lg/9706029">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> </div> </div> <p class="title is-5 mathjax"> Learning Parse and Translation Decisions From Examples With Rich Context </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Hermjakob%2C+U">Ulf Hermjakob</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="cmp-lg/9706029v1-abstract-short" style="display: inline;"> We propose a system for parsing and translating natural language that learns from examples and uses some background knowledge. As our parsing model we choose a deterministic shift-reduce type parser that integrates part-of-speech tagging and syntactic and semantic processing. Applying machine learning techniques, the system uses parse action examples acquired under supervision to generate a pa&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('cmp-lg/9706029v1-abstract-full').style.display = 'inline'; document.getElementById('cmp-lg/9706029v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="cmp-lg/9706029v1-abstract-full" style="display: none;"> We propose a system for parsing and translating natural language that learns from examples and uses some background knowledge. As our parsing model we choose a deterministic shift-reduce type parser that integrates part-of-speech tagging and syntactic and semantic processing. Applying machine learning techniques, the system uses parse action examples acquired under supervision to generate a parser in the form of a decision structure, a generalization of decision trees. To learn good parsing and translation decisions, our system relies heavily on context, as encoded in currently 205 features describing the morphological, syntactical and semantical aspects of a given parse state. Compared with recent probabilistic systems that were trained on 40,000 sentences, our system relies on more background knowledge and a deeper analysis, but radically fewer examples, currently 256 sentences. We test our parser on lexically limited sentences from the Wall Street Journal and achieve accuracy rates of 89.8% for labeled precision, 98.4% for part of speech tagging and 56.3% of test sentences without any crossing brackets. Machine translations of 32 Wall Street Journal sentences to German have been evaluated by 10 bilingual volunteers and been graded as 2.4 on a 1.0 (best) to 6.0 (worst) scale for both grammatical correctness and meaning preservation. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('cmp-lg/9706029v1-abstract-full').style.display = 'none'; document.getElementById('cmp-lg/9706029v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 30 June, 1997; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 1997. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">dissertation, 175 pages, LaTeX, 23 postscript figures, uses utthesis-compact.sty</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Report number:</span> TR 97-12 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/cmp-lg/9706002">arXiv:cmp-lg/9706002</a> <span>&nbsp;[<a href="https://arxiv.org/pdf/cmp-lg/9706002">pdf</a>, <a href="https://arxiv.org/ps/cmp-lg/9706002">ps</a>, <a href="https://arxiv.org/format/cmp-lg/9706002">other</a>]&nbsp;</span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computation and Language">cs.CL</span> </div> </div> <p class="title is-5 mathjax"> Learning Parse and Translation Decisions From Examples With Rich Context </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&amp;query=Hermjakob%2C+U">Ulf Hermjakob</a>, <a href="/search/cs?searchtype=author&amp;query=Mooney%2C+R+J">Raymond J. Mooney</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="cmp-lg/9706002v1-abstract-short" style="display: inline;"> We present a knowledge and context-based system for parsing and translating natural language and evaluate it on sentences from the Wall Street Journal. Applying machine learning techniques, the system uses parse action examples acquired under supervision to generate a deterministic shift-reduce parser in the form of a decision structure. It relies heavily on context, as encoded in features which&hellip; <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('cmp-lg/9706002v1-abstract-full').style.display = 'inline'; document.getElementById('cmp-lg/9706002v1-abstract-short').style.display = 'none';">&#9661; More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="cmp-lg/9706002v1-abstract-full" style="display: none;"> We present a knowledge and context-based system for parsing and translating natural language and evaluate it on sentences from the Wall Street Journal. Applying machine learning techniques, the system uses parse action examples acquired under supervision to generate a deterministic shift-reduce parser in the form of a decision structure. It relies heavily on context, as encoded in features which describe the morphological, syntactic, semantic and other aspects of a given parse state. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('cmp-lg/9706002v1-abstract-full').style.display = 'none'; document.getElementById('cmp-lg/9706002v1-abstract-short').style.display = 'inline';">&#9651; Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 5 June, 1997; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 1997. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">8 pages, LaTeX, 3 postscript figures, uses aclap.sty</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Proceedings of ACL/EACL&#39;97 </p> </li> </ol> <div 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