Datasets:

ljvmiranda921
/

tlunified-ner

Tasks:

Token Classification

Modalities:

Formats:

Sub-tasks:

named-entity-recognition

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ArXiv:

Tags:

named-entity-recognition

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Dataset card Data Studio Files Files and versions

ljvmiranda921 commited on Jul 17, 2023

Commit

53d8523

·

1 Parent(s): 5cee948

Fix grammar in the README

Files changed (3) hide show

README.md +1 -1
project.yml +1 -1
tlunified-ner.py +1 -1

README.md CHANGED Viewed

@@ -43,7 +43,7 @@ train-eval-index:
 ### Dataset Summary
 This dataset contains the annotated TLUnified corpora from Cruz and Cheng
-(2021).  It consists of a curated sample of around 7,000 documents for the
 named entity recognition (NER) task.  The majority of the corpus are news
 reports in Tagalog, resembling the domain of the original ConLL 2003.  There
 are three entity types: Person (PER), Organization (ORG), and Location (LOC).

 ### Dataset Summary
 This dataset contains the annotated TLUnified corpora from Cruz and Cheng
+(2021).  It is a curated sample of around 7,000 documents for the
 named entity recognition (NER) task.  The majority of the corpus are news
 reports in Tagalog, resembling the domain of the original ConLL 2003.  There
 are three entity types: Person (PER), Organization (ORG), and Location (LOC).

project.yml CHANGED Viewed

@@ -8,7 +8,7 @@ description: |
   ### Dataset Summary
   This dataset contains the annotated TLUnified corpora from Cruz and Cheng
-  (2021).  It consists of a curated sample of around 7,000 documents for the
   named entity recognition (NER) task.  The majority of the corpus are news
   reports in Tagalog, resembling the domain of the original ConLL 2003.  There
   are three entity types: Person (PER), Organization (ORG), and Location (LOC).

   ### Dataset Summary
   This dataset contains the annotated TLUnified corpora from Cruz and Cheng
+  (2021).  It is a curated sample of around 7,000 documents for the
   named entity recognition (NER) task.  The majority of the corpus are news
   reports in Tagalog, resembling the domain of the original ConLL 2003.  There
   are three entity types: Person (PER), Organization (ORG), and Location (LOC).

tlunified-ner.py CHANGED Viewed

@@ -6,7 +6,7 @@ logger = datasets.logging.get_logger(__name__)
 _DESCRIPTION = """
 This dataset contains the annotated TLUnified corpora from Cruz and Cheng
-(2021).  It consists of a curated sample of around 7,000 documents for the
 named entity recognition (NER) task.  The majority of the corpus are news
 reports in Tagalog, resembling the domain of the original ConLL 2003.  There
 are three entity types: Person (PER), Organization (ORG), and Location (LOC).

 _DESCRIPTION = """
 This dataset contains the annotated TLUnified corpora from Cruz and Cheng
+(2021). It is a curated sample of around 7,000 documents for the
 named entity recognition (NER) task.  The majority of the corpus are news
 reports in Tagalog, resembling the domain of the original ConLL 2003.  There
 are three entity types: Person (PER), Organization (ORG), and Location (LOC).