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--- pub-company:icon2009 [2009/10/20 23:21]
stranak
+++ pub-company:icon2009 [2010/03/25 10:01] (current)
stranak
@@ Line 32: / Line 32: @@
   * Link to the PDF version of the paper; link to Biblio?
-==== Out of Vocabulary ====
+===== Data =====
+==== IIIT Tides ====
+A dataset originally collected for the DARPA-TIDES surprise-language contest in 2002, later refined at IIIT Hyderabad and provided for the NLP Tools Contest at ICON 2008. For availability, enquire at the IIIT (http://ltrc.iiit.ac.in/). If you have the data, make sure that you have the same number of sentences and tokens. The Hindi side has been provided in two encodings, WX romanization and UTF-8. Although they should be equivalent, we always work with UTF-8.
+| **Part** | **Sentences** | **Tokens en** | **Bytes en** | **Tokens hi** | **Bytes hi** |
+| train |  50,000 |  1,195,436 |  6,496,995 |  1,287,174 |  15,917,598 |
+| dev |  1,000 |  21,842 |  118,239 |  23,851 |  291,147 |
+| test |  1,000 |  26,537 |  145,376 |  27,979 |  348,221 |
+The test data contain 1 reference translation per sentence.
+Our preprocessing of the data included the following steps:
+  * Further tokenization. Although Tides in the form we got it is roughly tokenized, there were tokens (like "anglo-american") we wished to split into smaller tokens.
+  * Unicode normalization. E.g., devanagari "z" was rewritten as "j"+"nukta".
+  * Cleaning. Sometimes a part of a sentence was removed but never a whole sentence, so the number of sentences is still the same.
+We are planning on making all the cleaning scripts available here. After preprocessing, the size of Tides changed as follows:
+| **Part** | **Sentences** | **Tokens en** | **Bytes en** | **Tokens hi** | **Bytes hi** |
+| train |  50,000 |  1,226,144 |  6,499,532 |  1,312,435 |  15,648,541 |
+| dev |  1,000 |  22,485 |  118,242 |  24,363 |  288,062 |
+| test |  1,000 |  27,169 |  145,528 |  28,574 |  343,288 |
+===== Out of Vocabulary =====
 No data have been lemmatised, so  all the numbers mean forms.
+^           Vocabulary Size               ^^^
 ^ data                ^ tokens  ^ types ^
 | **Tides-train-en**      | 1226144 | 48048 |
@@ Line 39: / Line 67: @@
 | **Tides+DP11-train-en** | 1402536 | 52947 |
 | **Tides+DP11-train-hi** | 1434543 | 57131 |
-| **Tides-dev-en**           | 22485 | 5596 |
+| **tides.train+dictfilt-en**  |  1227614  |  48349  |
-| **Tides-dev-hi**           | 24363 | 5642 |
+| **tides.train+dictfilt-hi**  |  1313857  |  53700  |
-| **Tides-test-en**          | 27169 | 5939 |
+| **tides.train+DP11+dictfilt-en**  |  1404006  |  53219  |
-| **Tides-test-hi**          | 28574 | 5872 |
+| **tides.train+DP11+dictfilt-hi**  |  1435965  |  57366  |
+| **set1-en**             |  247399 | 20869 |
+| **set1-hi**             |  201266 | 16442 |
+| **set2-en**             |  368732 | 23316 |
+| **set2-hi**             |  328553 | 20769 |
+| **set3-en**             |  303059 | 21819 |
+| **set3-hi**             |  272276 | 18178 |
+| **Tides-dev-en**        |   22485 |  5596 |
+| **Tides-dev-hi**        |   24363 |  5642 |
+| **Tides-test-en**       |   27169 |  5939 |
+| **Tides-test-hi**       |   28574 |  5872 |
+ - set1 = danielpipes-11+agrocorp-11+wikiner2008+wikiner2009+acl2005
+ - set2 = emille-11+danielpipes-11+agrocorp-11+wikiner2008+wikiner2009+acl2005
+ - set3 = emille-om+danielpipes-11+agrocorp-11+wikiner2008+wikiner2009+acl2005
+ - dictfilt = Shabdanjali from the web (with many errors, probably from wx-to-utf8). Filtered to get rid of the errors, then expanded entries with multiple meanings to separate entries, then filtered to keep onlu word that occur in the large Hindi monolingual corpus.
+^         Coverage               ^^^^^^^^^^^^^^^
+|                   | **tokens unseen in train**  |||||||  **types unseen in train**  |||||||
+|                   |  //Tides//  |  //Tides+DP// |  //Tides+dict// |  //Tides+DP+dict// |   //set1//       |  //set2//        |  //set3//        |  //Tides//      | //Tides+DP//    |  //Tides+dict// |  //Tides+DP+dict// |  //set1//        |  //set2 //       |  //set3//        |
+| **Tides-test-en** |   369       |     348       |  363 (1.336%)   |  343 (1.262%)      |  2524 (9.290%)   |  2330 (8.576%)   |  2429 (8.940%)   |    363          |       343       |  357 (6.011%)   |  338 (5.691%)      |  1974 (33.238%)  |  1824 (30.712%)  |  1901 (32.009%)  |
+| **Tides-test-hi** |   839       |     830       |  836 (2.926%)   |  828 (2.898%)      |  3480 (12.179%)  |  3233 (11.314%)  |  3310 (11.584%)  |   642           |       633       |  639 (10.882%)  |  631 (10.746%)     |  2569 (43.750%)  |  2412 (41.076%)  |  2465 (41.979%)  |
+| **Tides-dev-en**  |   464       |     421       |  462 (2.055%)   |  419 (1.863%)      |  2072 (9.215%)   |  1732 (7.703%)   |  1873 (8.330%)   |   459           |       418       |  457 (8.167%)   |  416 (7.434%)      |  1750 (31.272%)  |  1498 (26.769%)  |  1608 (28.735%)  |
+| **Tides-dev-hi**  |   619       |     607       |  618 (2.537%)   |  606 (2.487%)      | 2946 (12.092%)   |  2546 (10.450%)  |  2661 (10.922%)  |   580           |       568       |  579 (10.262%)  |  567 (10.050%)     |  2325 (41.209%)  |  2037 (36.104%)  |  2129 (37.735%)  |
-^         Coverage               ^^^^^
-|                | **tokens seen in train**|| **types seen in train**  ||
-|                |  //Tides//  | //Tides+DP//  |  //Tides//  |  //Tides+DP//  |
-| **Tides-test-en** |         |           |         |            |
-| **Tides-test-hi** |         |           |         |            |
-| **Tides-dev-en**  |         |           |         |            |
-| **Tides-dev-hi**  |         |           |         |            |

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