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README.md

@@ -1,84 +1,84 @@
----
-language:
-- fr
-license: cc-by-nc-4.0
-configs:
-- config_name: game_annotation
-  data_files:
-  - split: train
-    path: "RigorMortis_game_annotation.txt"
-- config_name: bonus_annotation
-  data_files:
-  - split: train
-    path: "RigorMortis_bonus_annotation.txt"
----
-
-> [!NOTE]
-> Dataset origin: https://github.com/gwaps4nlp/rigor-mortis/tree/master/LREC_2020
-
-## Description
-This page presents the annotated data described in the paper [**Rigor Mortis:Annotating MWEs with a Gamified Platform**](https://github.com/gwaps4nlp/rigor-mortis/blob/master/LREC_2020/LREC2020_RM.pdf) presented at LREC 2020 in Marseille.
-
-The annotation are described in two files:
- * `RigorMortis_game_annotation.txt` with the 504 sentences of the Annotation part
- * `RigorMortis_bonus_annotation.txt` with the 743 sentences of the Bonus Annotation part
-
-The annotations are presented by sentences, separated by a empty line with the format below:
-
-```
-# text : Lui et Bonassoli sont férus de science et avides de publicité .
-# number of players : 13
-# no mwe - 8 players (61.54%)
-# 1 : sont férus - 3 players (23.08%)
-# 2 : férus de - 2 players (15.38%)
-# 3 : avides de - 2 players (15.38%)
-1	Lui	_
-2	et	_
-3	Bonassoli	_
-4	sont	_	1
-5	férus	_	1;2
-6	de	_	2
-7	science	_
-8	et	_
-9	avides	_	3
-10	de	_	3
-11	publicité	_
-12	.	_
-```
-
-    
-## Citation
-```
-@inproceedings{fort-etal-2020-rigor,
-    title = "Rigor Mortis: Annotating {MWE}s with a Gamified Platform",
-    author = {Fort, Kar{\"e}n  and
-      Guillaume, Bruno  and
-      Pilatte, Yann-Alan  and
-      Constant, Mathieu  and
-      Lef{\`e}bvre, Nicolas},
-    editor = "Calzolari, Nicoletta  and
-      B{\'e}chet, Fr{\'e}d{\'e}ric  and
-      Blache, Philippe  and
-      Choukri, Khalid  and
-      Cieri, Christopher  and
-      Declerck, Thierry  and
-      Goggi, Sara  and
-      Isahara, Hitoshi  and
-      Maegaard, Bente  and
-      Mariani, Joseph  and
-      Mazo, H{\'e}l{\`e}ne  and
-      Moreno, Asuncion  and
-      Odijk, Jan  and
-      Piperidis, Stelios",
-    booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
-    month = may,
-    year = "2020",
-    address = "Marseille, France",
-    publisher = "European Language Resources Association",
-    url = "https://aclanthology.org/2020.lrec-1.541",
-    pages = "4395--4401",
-    abstract = "We present here Rigor Mortis, a gamified crowdsourcing platform designed to evaluate the intuition of the speakers, then train them to annotate multi-word expressions (MWEs) in French corpora. We previously showed that the speakers{'} intuition is reasonably good (65{\%} in recall on non-fixed MWE). We detail here the annotation results, after a training phase using some of the tests developed in the PARSEME-FR project.",
-    language = "English",
-    ISBN = "979-10-95546-34-4",
-}
+---
+language:
+- fra
+license: cc-by-nc-4.0
+configs:
+- config_name: game_annotation
+  data_files:
+  - split: train
+    path: "RigorMortis_game_annotation.txt"
+- config_name: bonus_annotation
+  data_files:
+  - split: train
+    path: "RigorMortis_bonus_annotation.txt"
+---
+
+> [!NOTE]
+> Dataset origin: https://github.com/gwaps4nlp/rigor-mortis/tree/master/LREC_2020
+
+## Description
+This page presents the annotated data described in the paper [**Rigor Mortis:Annotating MWEs with a Gamified Platform**](https://github.com/gwaps4nlp/rigor-mortis/blob/master/LREC_2020/LREC2020_RM.pdf) presented at LREC 2020 in Marseille.
+
+The annotation are described in two files:
+ * `RigorMortis_game_annotation.txt` with the 504 sentences of the Annotation part
+ * `RigorMortis_bonus_annotation.txt` with the 743 sentences of the Bonus Annotation part
+
+The annotations are presented by sentences, separated by a empty line with the format below:
+
+```
+# text : Lui et Bonassoli sont férus de science et avides de publicité .
+# number of players : 13
+# no mwe - 8 players (61.54%)
+# 1 : sont férus - 3 players (23.08%)
+# 2 : férus de - 2 players (15.38%)
+# 3 : avides de - 2 players (15.38%)
+1	Lui	_
+2	et	_
+3	Bonassoli	_
+4	sont	_	1
+5	férus	_	1;2
+6	de	_	2
+7	science	_
+8	et	_
+9	avides	_	3
+10	de	_	3
+11	publicité	_
+12	.	_
+```
+
+    
+## Citation
+```
+@inproceedings{fort-etal-2020-rigor,
+    title = "Rigor Mortis: Annotating {MWE}s with a Gamified Platform",
+    author = {Fort, Kar{\"e}n  and
+      Guillaume, Bruno  and
+      Pilatte, Yann-Alan  and
+      Constant, Mathieu  and
+      Lef{\`e}bvre, Nicolas},
+    editor = "Calzolari, Nicoletta  and
+      B{\'e}chet, Fr{\'e}d{\'e}ric  and
+      Blache, Philippe  and
+      Choukri, Khalid  and
+      Cieri, Christopher  and
+      Declerck, Thierry  and
+      Goggi, Sara  and
+      Isahara, Hitoshi  and
+      Maegaard, Bente  and
+      Mariani, Joseph  and
+      Mazo, H{\'e}l{\`e}ne  and
+      Moreno, Asuncion  and
+      Odijk, Jan  and
+      Piperidis, Stelios",
+    booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
+    month = may,
+    year = "2020",
+    address = "Marseille, France",
+    publisher = "European Language Resources Association",
+    url = "https://aclanthology.org/2020.lrec-1.541",
+    pages = "4395--4401",
+    abstract = "We present here Rigor Mortis, a gamified crowdsourcing platform designed to evaluate the intuition of the speakers, then train them to annotate multi-word expressions (MWEs) in French corpora. We previously showed that the speakers{'} intuition is reasonably good (65{\%} in recall on non-fixed MWE). We detail here the annotation results, after a training phase using some of the tests developed in the PARSEME-FR project.",
+    language = "English",
+    ISBN = "979-10-95546-34-4",
+}
 ```