Upload PET.py

PET.py

@@ -7,23 +7,57 @@ import datasets
 
 # Find for instance the citation on arxiv or on the dataset repo/website
 _CITATION = """\
-@article{DBLP:journals/corr/abs-2203-04860,
-  author    = {Patrizio Bellan and
-               Han van der Aa and
-               Mauro Dragoni and
-               Chiara Ghidini and
-               Simone Paolo Ponzetto},
-  title     = {{PET:} {A} new Dataset for Process Extraction from Natural Language
-               Text},
-  journal   = {CoRR},
-  volume    = {abs/2203.04860},
-  year      = {2022},
-  url       = {https://doi.org/10.48550/arXiv.2203.04860},
-  doi       = {10.48550/arXiv.2203.04860},
-  eprinttype = {arXiv},
-  eprint    = {2203.04860},
-  biburl    = {https://dblp.org/rec/journals/corr/abs-2203-04860.bib}
+@inproceedings{DBLP:conf/bpm/BellanADGP22,
+  author       = {Patrizio Bellan and
+                  Han van der Aa and
+                  Mauro Dragoni and
+                  Chiara Ghidini and
+                  Simone Paolo Ponzetto},
+  editor       = {Cristina Cabanillas and
+                  Niels Frederik Garmann{-}Johnsen and
+                  Agnes Koschmider},
+  title        = {{PET:} An Annotated Dataset for Process Extraction from Natural Language
+                  Text Tasks},
+  booktitle    = {Business Process Management Workshops - {BPM} 2022 International Workshops,
+                  M{\"{u}}nster, Germany, September 11-16, 2022, Revised Selected
+                  Papers},
+  series       = {Lecture Notes in Business Information Processing},
+  volume       = {460},
+  pages        = {315--321},
+  publisher    = {Springer},
+  year         = {2022},
+  url          = {https://doi.org/10.1007/978-3-031-25383-6\_23},
+  doi          = {10.1007/978-3-031-25383-6\_23},
+  timestamp    = {Tue, 14 Feb 2023 09:47:10 +0100},
+  biburl       = {https://dblp.org/rec/conf/bpm/BellanADGP22.bib},
+  bibsource    = {dblp computer science bibliography, https://dblp.org}
 }
+@inproceedings{DBLP:conf/aiia/BellanGDPA22,
+  author       = {Patrizio Bellan and
+                  Chiara Ghidini and
+                  Mauro Dragoni and
+                  Simone Paolo Ponzetto and
+                  Han van der Aa},
+  editor       = {Debora Nozza and
+                  Lucia C. Passaro and
+                  Marco Polignano},
+  title        = {Process Extraction from Natural Language Text: the {PET} Dataset and
+                  Annotation Guidelines},
+  booktitle    = {Proceedings of the Sixth Workshop on Natural Language for Artificial
+                  Intelligence {(NL4AI} 2022) co-located with 21th International Conference
+                  of the Italian Association for Artificial Intelligence (AI*IA 2022),
+                  Udine, November 30th, 2022},
+  series       = {{CEUR} Workshop Proceedings},
+  volume       = {3287},
+  pages        = {177--191},
+  publisher    = {CEUR-WS.org},
+  year         = {2022},
+  url          = {https://ceur-ws.org/Vol-3287/paper18.pdf},
+  timestamp    = {Fri, 10 Mar 2023 16:23:01 +0100},
+  biburl       = {https://dblp.org/rec/conf/aiia/BellanGDPA22.bib},
+  bibsource    = {dblp computer science bibliography, https://dblp.org}
+}
+
 """
 
 # You can copy an official description
@@ -35,9 +69,18 @@ _HOMEPAGE = "https://pdi.fbk.eu/pet-dataset/"
 
 _LICENSE = "MIT"
 
-_URL = "https://pdi.fbk.eu/pet/PETHuggingFace/"
-_TEST_FILE = "test.json"
-_TEST_FILE_RELATIONS = 'PETrelations.json'
+_URL_11 = "https://raw.githubusercontent.com/patriziobellan86/PETv1.1/master/"
+_URL_10 = "https://pdi.fbk.eu/pet/PETHuggingFace/"
+_TEST_FILE_11 = "PETv1.1-entities.jsonl"
+_TEST_FILE_10 = "test.json"
+_TEST_FILE_RELATIONS_11 = "PETv1.1-relations.json"
+_TEST_FILE_RELATIONS_10 = 'PETrelations.json'
+
+
+
+
+
+
 
 _NER = 'token-classification'
 _RELATIONS_EXTRACTION = 'relations-extraction'
@@ -107,6 +150,16 @@ class PET(datasets.GeneratorBasedBuilder):
                             version=datasets.Version("1.0.1"),
                             description="The PET Dataset for Relation Extraction"
                             ),
+                        # PETConfig(
+                        #     name=_NER,
+                        #     version=datasets.Version("1.1.0"),
+                        #     description="The PET Dataset for Token Classification"
+                        #     ),
+                        # PETConfig(
+                        #     name=_RELATIONS_EXTRACTION,
+                        #     version=datasets.Version("1.1.0"),
+                        #     description="The PET Dataset for Relation Extraction"
+                        #     ),
                         ]
 
     DEFAULT_CONFIG_NAME = _RELATIONS_EXTRACTION
@@ -136,10 +189,17 @@ class PET(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
+        print(f"{self.config.version}")
         if self.config.name == _NER:
-            urls_to_download = {
-                "test": f"{_URL}{_TEST_FILE}",
-            }
+            if self.config.version=='1.0.1':
+                urls_to_download = {
+                        "test": f"{_URL_10}{_TEST_FILE_10}",
+                    }
+            else:
+                urls_to_download = {
+                    "test": f"{_URL_11}{_TEST_FILE_11}",
+                }
+
             downloaded_files = dl_manager.download_and_extract(urls_to_download)
             return [datasets.SplitGenerator(
                         name=datasets.Split.TEST,
@@ -150,9 +210,14 @@ class PET(datasets.GeneratorBasedBuilder):
                         },
                     )]
         else:
-            urls_to_download = {
-                "test": f"{_URL}{_TEST_FILE_RELATIONS}",
-            }
+            if self.config.version=='1.0.1':
+                urls_to_download = {
+                        "test": f"{_URL_10}{_TEST_FILE_RELATIONS_10}",
+                    }
+            else:
+                urls_to_download = {
+                    "test": f"{_URL_11}{_TEST_FILE_RELATIONS_11}",
+                }
             downloaded_files = dl_manager.download_and_extract(urls_to_download)
             return [datasets.SplitGenerator(
                 name=datasets.Split.TEST,