Update ESSAI.py

ESSAI.py

@@ -46,8 +46,7 @@ class ESSAI(datasets.GeneratorBasedBuilder):
     BUILDER_CONFIGS = [
         datasets.BuilderConfig(name="pos", version="1.0.0", description="The ESSAI corpora - POS Speculation task"),
 
-        datasets.BuilderConfig(name="cls_spec", version="1.0.0", description="The ESSAI corpora - CLS Speculation task"),
-        datasets.BuilderConfig(name="cls_neg", version="1.0.0", description="The ESSAI corpora - CLS Negation task"),
+        datasets.BuilderConfig(name="cls", version="1.0.0", description="The ESSAI corpora - CLS Negation / Speculation task"),
 
         datasets.BuilderConfig(name="ner_spec", version="1.0.0", description="The ESSAI corpora - NER Speculation task"),
         datasets.BuilderConfig(name="ner_neg", version="1.0.0", description="The ESSAI corpora - NER Negation task"),
@@ -63,10 +62,9 @@ class ESSAI(datasets.GeneratorBasedBuilder):
                     "document_id": datasets.Value("string"),
                     "tokens": [datasets.Value("string")],
                     "lemmas": [datasets.Value("string")],
-                    "pos_tags": [datasets.Value("string")],
-                    # "pos_tags": [datasets.features.ClassLabel(
-                    #     names = ['VER:pper', 'VER:subi', 'VER:cond', 'INT', 'VER:infi', 'PUN:cit', 'ITAC', 'PUN', 'VER:ppre', 'VER:pres', 'PRO:REL', 'ADJ', 'VER:subp', 'NN', 'PREF', 'PRP', 'PRO:IND', 'PRO:POS', 'DET:POS', 'VER:futu', 'PRO:DEM', 'KON', 'DET:ART', 'VER:', 'PRP:det', 'PRO', 'FAG', 'NOM', 'SYM', 'VER:impf', 'CIT02-HM', 'SENT', 'Bayer', 'VER:simp', 'ADV', 'bayer', '@card@', 'PRO:PER', 'NUM', 'ABR', 'NAM'],
-                    # )],
+                    "pos_tags": [datasets.features.ClassLabel(
+                        names = ['INT', 'PRO:POS', 'PRP', 'SENT', 'PRO', 'ABR', 'VER:pres', 'KON', 'SYM', 'DET:POS', 'VER:', 'PRO:IND', 'NAM', 'ADV', 'PRO:DEM', 'NN', 'PRO:PER', 'VER:pper', 'VER:ppre', 'PUN', 'VER:simp', 'PREF', 'NUM', 'VER:futu', 'NOM', 'VER:impf', 'VER:subp', 'VER:infi', 'DET:ART', 'PUN:cit', 'ADJ', 'PRP:det', 'PRO:REL', 'VER:cond', 'VER:subi'],
+                    )],
                 }
             )
         
@@ -77,25 +75,28 @@ class ESSAI(datasets.GeneratorBasedBuilder):
                     "id": datasets.Value("string"),
                     "document_id": datasets.Value("string"),
                     "tokens": [datasets.Value("string")],
-                    "label": datasets.Value("string"),
-                    # "label": datasets.features.ClassLabel(
-                    #     names = ['VER:pper', 'VER:subi', 'VER:cond', 'INT', 'VER:infi', 'PUN:cit', 'ITAC', 'PUN', 'VER:ppre', 'VER:pres', 'PRO:REL', 'ADJ', 'VER:subp', 'NN', 'PREF', 'PRP', 'PRO:IND', 'PRO:POS', 'DET:POS', 'VER:futu', 'PRO:DEM', 'KON', 'DET:ART', 'VER:', 'PRP:det', 'PRO', 'FAG', 'NOM', 'SYM', 'VER:impf', 'CIT02-HM', 'SENT', 'Bayer', 'VER:simp', 'ADV', 'bayer', '@card@', 'PRO:PER', 'NUM', 'ABR', 'NAM'],
-                    # ),
+                    "label": datasets.features.ClassLabel(
+                        names = ['negation_speculation', 'negation', 'neutral', 'speculation'],
+                    ),
                 }
             )
         
         elif self.config.name.find("ner") != -1:
 
+            if self.config.name.find("_spec") != -1:
+                names = ['O', 'B_cue_spec', 'B_scope_spec', 'I_scope_spec']
+            elif self.config.name.find("_neg") != -1:
+                names = ['O', 'B_cue_neg', 'B_scope_neg', 'I_scope_neg']
+
             features = datasets.Features(
                 {
                     "id": datasets.Value("string"),
                     "document_id": datasets.Value("string"),
                     "tokens": [datasets.Value("string")],
                     "lemmas": [datasets.Value("string")],
-                    "ner_tags": [datasets.Value("string")],
-                    # "ner_tags": [datasets.features.ClassLabel(
-                    #     names = ['VER:pper', 'VER:subi', 'VER:cond', 'INT', 'VER:infi', 'PUN:cit', 'ITAC', 'PUN', 'VER:ppre', 'VER:pres', 'PRO:REL', 'ADJ', 'VER:subp', 'NN', 'PREF', 'PRP', 'PRO:IND', 'PRO:POS', 'DET:POS', 'VER:futu', 'PRO:DEM', 'KON', 'DET:ART', 'VER:', 'PRP:det', 'PRO', 'FAG', 'NOM', 'SYM', 'VER:impf', 'CIT02-HM', 'SENT', 'Bayer', 'VER:simp', 'ADV', 'bayer', '@card@', 'PRO:PER', 'NUM', 'ABR', 'NAM'],
-                    # )],
+                    "ner_tags": [datasets.features.ClassLabel(
+                        names = names,
+                    )],
                 }
             )
 
@@ -150,10 +151,10 @@ class ESSAI(datasets.GeneratorBasedBuilder):
 
         unique_id_doc = []
 
-        if self.config.name.find("pos") != -1:
-            docs = ["ESSAI_neg.txt", "ESSAI_spec.txt"]
-        else:
+        if self.config.name.find("ner") != -1:
             docs = [f"ESSAI_{subset}.txt"]
+        else:
+            docs = ["ESSAI_neg.txt", "ESSAI_spec.txt"]
 
         for file in docs:
 
@@ -182,7 +183,10 @@ class ESSAI(datasets.GeneratorBasedBuilder):
                         
                         if tag == "@card@":
                             print(splitted)
-                        
+
+                        if word == "@card@":
+                            print(splitted)
+
                         if lemma == "000" and tag == "@card@":
                             tag = "NUM"
                             word = "100 000"
@@ -244,12 +248,15 @@ class ESSAI(datasets.GeneratorBasedBuilder):
 
                         id_doc, id_word, word, lemma, _ = line.split("\t")[0:5]
                         tag = line.replace("\n","").split("\t")[-1]
+
                         if tag == "***" or tag == "_":
                             tag = "O"
                         elif tag == "v":
                             tag = "I_scope_spec"
                         elif tag == "z":
                             tag = "O"
+                        elif tag == "I_scope_spec_":
+                            tag = "I_scope_spec"
 
                         id_docs.append(id_doc)
                         id_words.append(id_word)
@@ -291,9 +298,7 @@ class ESSAI(datasets.GeneratorBasedBuilder):
                 ]
                 f_in.close()
 
-                classe = "negation" if self.config.name.find("neg") != -1 else "speculation"
-
-                all_res = []
+                classe = "negation" if filename.find("_neg") != -1 else "speculation"
 
                 for document in conll:
 
@@ -303,20 +308,40 @@ class ESSAI(datasets.GeneratorBasedBuilder):
                     identifier = document[0][0]
 
                     unique = list(set([w[-1] for w in document]))
-                    # print(document)
                     tokens = [sent[2] for sent in document if len(sent) > 1]
 
                     if "***" in unique:
-                        l = "none"
+                        l = "neutral"
                     elif "_" in unique:
                         l = classe
 
-                    all_res.append({
-                        "id": str(identifier),
-                        "document_id": identifier,
-                        "tokens": tokens,
-                        "label": l,
-                    })
+                    if identifier in unique_id_doc and l == 'neutral':
+                        continue
+
+                    elif identifier in unique_id_doc and l != 'neutral':
+
+                        index_l = unique_id_doc.index(identifier)
+
+                        if all_res[index_l]["label"] != "neutral":
+                            l = "negation_speculation"
+
+                        all_res[index_l] = {
+                            "id": str(identifier),
+                            "document_id": identifier,
+                            "tokens": tokens,
+                            "label": l,
+                        }
+
+                    else:
+
+                        all_res.append({
+                            "id": str(identifier),
+                            "document_id": identifier,
+                            "tokens": tokens,
+                            "label": l,
+                        })
+
+                        unique_id_doc.append(identifier)
 
         ids = [r["id"] for r in all_res]