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22 August 2003CLEF 2003 The 2003 TIDES Surprise Language Exercise Douglas W. Oard University of Maryland
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Outline Thinking out of the box Some results Lesson Learned
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Surprise Language Framework Zero-resource start (treasure hunt) Time constrained (10 or 29 days) English Users / Documents in language X Character-coded text Research-oriented Intensely collaborative (team-based)
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Schedule Cebuano Announce: Mar 5 Test Data: Stop Work: Mar 14 Newsletter:April Talks:May 30 (HLT) Papers: Hindi Jun 1 Jun 27 Jun 30 August Aug 5 (TIDES PI) Aug 15 (TALIP)
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16 Participating Teams Cebuano and Hindi ISI Maryland NYU Johns Hopkins Sheffield LDC CMU UC Berkeley MITRE Hindi Only U Mass Alias-i BBN IBM CUNY KAT SPAWAR
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Five evaluated tasks –Automatic CLIR (English queries) –Topic tracking (English examples, event-based) –Machine translation into English –English “Headline” generation –Entity tagging (five MUC types) Several useful components –POS tags, morphology, time expressions, parsing Several demonstration systems –Interactive CLIR (two systems) –Cross-language QA (English Q, Translated A) –Machine translation (+ Translation elicitation) –Cross-document entity tracking
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Hindi Participants Alias-I UC Berkeley BBN CMU CUNY Johns Hopkins IBM ISI LDC MITRE NYU SPAWAR U. Sheffield U. Massachusetts U. Maryland Resource Generation Detection Extraction Summarization Translation
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Detection Extraction Summarization Books Web Books Web People Lexicons Corpora Time Resource Harvesting Systems Research Results Capture Process Knowledge Innovation Cycle Coordination Strategy Push Organize Talk
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The Synchronization Challenge
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Cebuano MT Results Bible Cebuano book Dict Melamed News
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Cebuano Interactive CLIR Starting Point: iCLEF 2002 system (German) –Interface: “synonyms”/examples (parallel)/MT –Back end: InQuery/Pirkola’s method 3-day porting effort –Cebuano indexing (no stemming) –One-best gloss translation (bilingual term list) Informal Evaluation –2 Cebuano native speakers (at ISI)
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Hindi syntax is generally very “regular” Subject – Object – Verb is the preferred order –John saw Mary.= जॉन ने मेरी को देखा । Presence of (occasionally deleted) case markers often permit reordering –John saw Mary.= मेरी को जॉन ने देखा । English (or western) punctuation is pervasive in many modern texts –John said, “ I am here ” = जॉन ने कहा, “ मैं यहाँ हूँ ” The subject may be omitted in some contexts –A: Where is John?B: [He] went home. – अ : जॉन कहाँ है ? ब : [ वह ] घर चला गया।
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Hindi Encoding Text encoding for storage and transmission and text rendering for display and printing are separated Which syllable constituents get their own code-points? –Several 8-bit encodings: After assigning a code point to each stand-alone vowel and full consonant, and to half-consonants and vowels within a syllable, spare code-points get used for assorted/frequent CC clusters. –Unicode UTF-16: Only stand-alone vowels, full consonants and vowels within syllables have their own code-points. All half consonants are realized by a `full consonant + halant’ sequence Choice of the “grammar” for syllable construction and rendering? –Several 8-bit encodings write the code-points in display order, simplifying the rendering program –Unicode writes it in pronunciation order, making for a considerably more complex display program
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Hindi Week 1: Porting Monday –2,973 BBC documents (UTF-8) –Batch CLIR (no stem, 2/3 known items rank 1) Tuesday –MIRACLE (“ITRANS”, gloss) –Stemmer (implemented from a paper) Wednesday –BBC CLIR collection (19 topic, known item) Friday: –Parallel text (Bible: 900k words, Web: 4k words) –Devanagari OCR system
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Hindi Weeks 2/3/4: Exploration N-grams (trigrams best for UTF-8) Relative Average Term Frequency (Kwok) Scanned bilingual dictionary (Oxford) More topics for test collection (29) Weighted structured queries (IBM lexicon) Alternative stemmers (U Mass, Berkeley) Blind relevance feedback Transliteration Noun phrase translation MIRACLE integration (ISI MT, BBN headlines)
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Formative Evaluation
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Transliteration Importance: Names, loan words – दक्षिण कोरिया (Dakshin Korea) Pronunciation crosswalk English->Hindi –English pronunciation (Festival) –Overgenerate Hindi characters (hand-built rules) Doctor => d aa k t ax r OR d ao k t ax r –Rank n-best using bigrams (Hindi name list) Treat as alternate translations for CLIR –Pirkola’s method
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Some Challenges Formative evaluation Synchronize variable-rate efforts –Soccer, not football Integration Capturing lessons learned –See the forest, not just the trees
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For More Information TIDES Newsletter –Cebuano: April –Hindi: August Papers –NAACL/HLT Short paper –MT Summit (late Sep) –ACM TALIP Special Issue Demonstration systems –Contact individual sites
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