add updated README.md

README.md

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- expert-generated
+language:
+- am
+- bbj
+- bm
+- ee
+- ha
+- ig
+- lg
+- luo
+- mos
+- ny
+- pcm
+- rw
+- sn
+- sw
+- tn
+- tw
+- wo
+- xh
+- yo
+- zu
+license:
+- unknown
+multilinguality:
+- multilingual
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+task_categories:
+- token-classification
+task_ids:
+- named-entity-recognition
+pretty_name: MasakhaNER-X
+dataset_info:
+- config_name: am
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1441
+  - name: validation
+    num_examples: 250
+  - name: test
+    num_examples: 500
+- config_name: bbj
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1441
+  - name: validation
+    num_examples: 483
+  - name: test
+    num_examples: 966
+- config_name: bm
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1441
+  - name: validation
+    num_examples: 638
+  - name: test
+    num_examples: 1000
+- config_name: ee
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1441
+  - name: validation
+    num_examples: 501
+  - name: test
+    num_examples: 1000
+- config_name: ha
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1441
+  - name: validation
+    num_examples: 272
+  - name: test
+    num_examples: 545
+- config_name: ig
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1441
+  - name: validation
+    num_examples: 1000
+  - name: test
+    num_examples: 1000
+- config_name: lg
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1441
+  - name: validation
+    num_examples: 906
+  - name: test
+    num_examples: 1000
+- config_name: luo
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 644
+  - name: validation
+    num_examples: 92
+  - name: test
+    num_examples: 185
+- config_name: mos
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1441
+  - name: validation
+    num_examples: 648
+  - name: test
+    num_examples: 1000
+- config_name: ny
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1441
+  - name: validation
+    num_examples: 893
+  - name: test
+    num_examples: 1000
+- config_name: pcm
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1441
+  - name: validation
+    num_examples: 1000
+  - name: test
+    num_examples: 1000
+- config_name: rw
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1441
+  - name: validation
+    num_examples: 1000
+  - name: test
+    num_examples: 1000
+- config_name: sn
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1441
+  - name: validation
+    num_examples: 887
+  - name: test
+    num_examples: 1000
+- config_name: sw
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1441
+  - name: validation
+    num_examples: 1000
+  - name: test
+    num_examples: 1000
+- config_name: tn
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1441
+  - name: validation
+    num_examples: 499
+  - name: test
+    num_examples: 996
+- config_name: tw
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1441
+  - name: validation
+    num_examples: 605
+  - name: test
+    num_examples: 1000
+- config_name: wo
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1441
+  - name: validation
+    num_examples: 923
+  - name: test
+    num_examples: 1000
+- config_name: xh
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1441
+  - name: validation
+    num_examples: 817
+  - name: test
+    num_examples: 1000
+- config_name: yo
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1441
+  - name: validation
+    num_examples: 1000
+  - name: test
+    num_examples: 1000
+- config_name: zu
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: spans
+    sequence: string
+  - name: target
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1441
+  - name: validation
+    num_examples: 836
+  - name: test
+    num_examples: 1000
+config_names:
+- am
+- bbj
+- bm
+- ee
+- ha
+- ig
+- lg
+- luo
+- mos
+- ny
+- pcm
+- rw
+- sn
+- sw
+- tn
+- tw
+- wo
+- xh
+- yo
+- zu
+---
+
+# Dataset Card for MasakhaNER
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** [homepage](https://github.com/masakhane-io/masakhane-ner/tree/main/xtreme-up/MasakhaNER-X)
+- **Repository:** [github](https://github.com/masakhane-io/masakhane-ner/tree/main/xtreme-up/MasakhaNER-X)
+- **Paper:** [paper](https://aclanthology.org/2022.emnlp-main.298)
+- **Point of Contact:** [Masakhane](https://www.masakhane.io/) or didelani@lsv.uni-saarland.de
+
+### Dataset Summary
+
+MasakhaNER-X is an aggregation of MasakhaNER 1.0 and MasakhaNER 2.0 datasets for 20 African languages. The dataset is not in CoNLL format. The input is the original raw text while the output is byte-level span annotations.
+
+Example:
+{"example_id": "test-00015916", "language": "pcm", "text": "By Bashir Ibrahim Hassan", "spans": [{"start_byte": 3, "limit_byte": 24, "label": "PER"}], "target": "PER: Bashir Ibrahim Hassan"}
+
+MasakhaNER-X is a named entity dataset consisting of PER, ORG, LOC, and DATE entities annotated by Masakhane for twenty African languages:
+- Amharic
+- Ghomala
+- Bambara
+- Ewe
+- Hausa
+- Igbo
+- Kinyarwanda
+- Luganda
+- Luo
+- Mossi
+- Chichewa
+- Nigerian-Pidgin
+- chiShona
+- Swahili
+- Setswana
+- Twi
+- Wolof
+- Xhosa
+- Yoruba
+- Zulu
+
+The train/validation/test sets are available for all the twenty languages.
+
+For more details see https://aclanthology.org/2022.emnlp-main.298
+
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+- `named-entity-recognition`: The performance in this task is measured with [Span F1](https://github.com/google-research/multilingual-t5/blob/9dcd60fc43c31a8651461f9a21894a134ba22166/multilingual_t5/evaluation/metrics.py#L123) (higher is better). A named entity is correct only if it is an exact match of the corresponding entity in the data.
+
+### Languages
+
+There are twenty languages available :
+- Amharic (am)
+- Ghomala (bbj)
+- Bambara (bm)
+- Ewe (ee)
+- Hausa (ha)
+- Igbo (ig)
+- Kinyarwanda (rw)
+- Luganda (lg)
+- Luo (luo)
+- Mossi (mos)
+- Chichewa (ny)
+- Nigerian-Pidgin (pcm)
+- chiShona (sn)
+- Swahili (sw)
+- Setswana (tn)
+- Twi (tw)
+- Wolof (wo)
+- Xhosa (xh)
+- Yoruba (yo)
+- Zulu (zu)
+
+## Dataset Structure
+
+### Data Instances
+
+The examples look like this for Nigerian-Pidgin:
+
+```
+from datasets import load_dataset
+data = load_dataset('masakhaner-x', 'pcm') 
+
+# Please, specify the language code
+
+# A data point consists of sentences seperated by empty line and tab-seperated tokens and tags. 
+{'id': '0',
+ 'text': "Most of de people who dey opposed to Prez Akufo-Addo en decision say within 3 weeks of lockdown, total number of cases for Ghana rise from around 100 catch 1024.",
+ 'spans': [{"start_byte": 42, "limit_byte": 52, "label": "PER"}, {"start_byte": 76, "limit_byte": 83, "label": "DATE"}, {"start_byte": 123, "limit_byte": 128, "label": "LOC"}]
+ 'target': "PER: Akufo-Addo $$ DATE: 3 weeks $$ LOC: Ghana"
+}
+
+```
+
+### Data Fields
+
+- `id`: id of the sample
+- `text`: sentence containing entities
+- `spans`: details of each named entities in the sentence
+- `target`: named entities and their values. Each named entity is separated by '$$'
+
+The NER tags correspond to this list:
+```
+"PER", "ORG", "LOC", and "DATE",
+```
+
+### Data Splits
+
+For all languages, there are three splits - `train`, `validation` and `test` splits.
+
+The splits have the following sizes :
+
+| Language        | train | validation | test |
+|-----------------|------:|-----------:|-----:|
+| Amharic         |  1441 |        250 |  500 |
+| Gbomola         |  1441 |        483 |  966 |
+| Bambara         |  1441 |        638 |  1000|
+| Ewe             |  1441 |        501 |  1000|
+| Hausa           |  1441 |        1000|  1000|
+| Igbo            |  1441 |        319 |  638 |
+| Kinyarwanda     |  1441 |        1000|  1000|
+| Luganda         |  1441 |        906 |  1000|
+| Luo             |  644  |         92 |  185 |
+| Mossi           |  1441 |        648 |  1000|
+| Chichewa        |  1441 |        893 |  1000|
+| Nigerian-Pidgin |  1441 |        1000|  1000|
+| Shona           |  1441 |        887 |  1000|
+| Swahili         |  1441 |        1000|  1000|
+| Setswana        |  1441 |        499 |  996 |
+| Twi             |  1441 |        605 |  1000|
+| Wolof           |  1441 |        923 |  1000|
+| Xhosa           |  1441 |        817 |  1000|
+| Yoruba          |  1441 |        1000|  1000|
+| Zulu            |  1441 |        836 |  1000|
+
+
+### Licensing Information
+
+The licensing status of the data is CC 4.0 Non-Commercial
+
+### Citation Information
+
+Provide the [BibTex](http://www.bibtex.org/)-formatted reference for the dataset. For example:
+```
+@inproceedings{adelani-etal-2022-masakhaner,
+    title = "{M}asakha{NER} 2.0: {A}frica-centric Transfer Learning for Named Entity Recognition",
+    author = "Adelani, David  and
+      Neubig, Graham  and
+      Ruder, Sebastian  and
+      Rijhwani, Shruti  and
+      Beukman, Michael  and
+      Palen-Michel, Chester  and
+      Lignos, Constantine  and
+      Alabi, Jesujoba  and
+      Muhammad, Shamsuddeen  and
+      Nabende, Peter  and
+      Dione, Cheikh M. Bamba  and
+      Bukula, Andiswa  and
+      Mabuya, Rooweither  and
+      Dossou, Bonaventure F. P.  and
+      Sibanda, Blessing  and
+      Buzaaba, Happy  and
+      Mukiibi, Jonathan  and
+      Kalipe, Godson  and
+      Mbaye, Derguene  and
+      Taylor, Amelia  and
+      Kabore, Fatoumata  and
+      Emezue, Chris Chinenye  and
+      Aremu, Anuoluwapo  and
+      Ogayo, Perez  and
+      Gitau, Catherine  and
+      Munkoh-Buabeng, Edwin  and
+      Memdjokam Koagne, Victoire  and
+      Tapo, Allahsera Auguste  and
+      Macucwa, Tebogo  and
+      Marivate, Vukosi  and
+      Elvis, Mboning Tchiaze  and
+      Gwadabe, Tajuddeen  and
+      Adewumi, Tosin  and
+      Ahia, Orevaoghene  and
+      Nakatumba-Nabende, Joyce  and
+      Mokono, Neo Lerato  and
+      Ezeani, Ignatius  and
+      Chukwuneke, Chiamaka  and
+      Oluwaseun Adeyemi, Mofetoluwa  and
+      Hacheme, Gilles Quentin  and
+      Abdulmumin, Idris  and
+      Ogundepo, Odunayo  and
+      Yousuf, Oreen  and
+      Moteu, Tatiana  and
+      Klakow, Dietrich",
+    booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
+    month = dec,
+    year = "2022",
+    address = "Abu Dhabi, United Arab Emirates",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2022.emnlp-main.298",
+    pages = "4488--4508",
+    abstract = "African languages are spoken by over a billion people, but they are under-represented in NLP research and development. Multiple challenges exist, including the limited availability of annotated training and evaluation datasets as well as the lack of understanding of which settings, languages, and recently proposed methods like cross-lingual transfer will be effective. In this paper, we aim to move towards solutions for these challenges, focusing on the task of named entity recognition (NER). We present the creation of the largest to-date human-annotated NER dataset for 20 African languages. We study the behaviour of state-of-the-art cross-lingual transfer methods in an Africa-centric setting, empirically demonstrating that the choice of source transfer language significantly affects performance. While much previous work defaults to using English as the source language, our results show that choosing the best transfer language improves zero-shot F1 scores by an average of 14{\%} over 20 languages as compared to using English.",
+}
+```