Description
Onto is a Named Entity Recognition (or NER) model trained on OntoNotes 5.0. It can extract up to 18 entities such as people, places, organizations, money, time, date, etc.
This model uses the pretrained bert_large_cased embeddings model from the BertEmbeddings annotator as an input.
Predicted Entities
CARDINAL, DATE, EVENT, FAC, GPE, LANGUAGE, LAW, LOC, MONEY, NORP, ORDINAL, ORG, PERCENT, PERSON, PRODUCT, QUANTITY, TIME, WORK_OF_ART.
Live Demo Open in Colab Download Copy S3 URI
How to use
...
embeddings = BertEmbeddings.pretrained("bert_large_cased", "en") \
.setInputCols("sentence", "token") \
.setOutputCol("embeddings")
ner_onto = NerDLModel.pretrained("onto_bert_large_cased", "en") \
.setInputCols(["document", "token", "embeddings"]) \
.setOutputCol("ner")
...
nlp_pipeline = Pipeline(stages=[document_assembler, sentence_detector, tokenizer, embeddings, ner_onto, ner_converter])
pipeline_model = nlp_pipeline.fit(spark.createDataFrame([['']]).toDF('text'))
result = pipeline_model.transform(spark.createDataFrame([["William Henry Gates III (born October 28, 1955) is an American business magnate, software developer, investor, and philanthropist. He is best known as the co-founder of Microsoft Corporation. During his career at Microsoft, Gates held the positions of chairman, chief executive officer (CEO), president and chief software architect, while also being the largest individual shareholder until May 2014. He is one of the best-known entrepreneurs and pioneers of the microcomputer revolution of the 1970s and 1980s. Born and raised in Seattle, Washington, Gates co-founded Microsoft with childhood friend Paul Allen in 1975, in Albuquerque, New Mexico; it went on to become the world's largest personal computer software company. Gates led the company as chairman and CEO until stepping down as CEO in January 2000, but he remained chairman and became chief software architect. During the late 1990s, Gates had been criticized for his business tactics, which have been considered anti-competitive. This opinion has been upheld by numerous court rulings. In June 2006, Gates announced that he would be transitioning to a part-time role at Microsoft and full-time work at the Bill & Melinda Gates Foundation, the private charitable foundation that he and his wife, Melinda Gates, established in 2000. He gradually transferred his duties to Ray Ozzie and Craig Mundie. He stepped down as chairman of Microsoft in February 2014 and assumed a new post as technology adviser to support the newly appointed CEO Satya Nadella."]], ["text"]))
...
val embeddings = BertEmbeddings.pretrained("bert_large_cased", "en")
.setInputCols(Array("sentence", "token"))
.setOutputCol("embeddings")
val ner_onto = NerDLModel.pretrained("onto_bert_large_cased", "en")
.setInputCols(Array("document", "token", "embeddings"))
.setOutputCol("ner")
...
val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, tokenizer, embeddings, ner_onto, ner_converter))
val data = Seq("William Henry Gates III (born October 28, 1955) is an American business magnate, software developer, investor, and philanthropist. He is best known as the co-founder of Microsoft Corporation. During his career at Microsoft, Gates held the positions of chairman, chief executive officer (CEO), president and chief software architect, while also being the largest individual shareholder until May 2014. He is one of the best-known entrepreneurs and pioneers of the microcomputer revolution of the 1970s and 1980s. Born and raised in Seattle, Washington, Gates co-founded Microsoft with childhood friend Paul Allen in 1975, in Albuquerque, New Mexico; it went on to become the world's largest personal computer software company. Gates led the company as chairman and CEO until stepping down as CEO in January 2000, but he remained chairman and became chief software architect. During the late 1990s, Gates had been criticized for his business tactics, which have been considered anti-competitive. This opinion has been upheld by numerous court rulings. In June 2006, Gates announced that he would be transitioning to a part-time role at Microsoft and full-time work at the Bill & Melinda Gates Foundation, the private charitable foundation that he and his wife, Melinda Gates, established in 2000. He gradually transferred his duties to Ray Ozzie and Craig Mundie. He stepped down as chairman of Microsoft in February 2014 and assumed a new post as technology adviser to support the newly appointed CEO Satya Nadella.").toDF("text")
val result = pipeline.fit(data).transform(data)
import nlu
text = ["""William Henry Gates III (born October 28, 1955) is an American business magnate, software developer, investor, and philanthropist. He is best known as the co-founder of Microsoft Corporation. During his career at Microsoft, Gates held the positions of chairman, chief executive officer (CEO), president and chief software architect, while also being the largest individual shareholder until May 2014. He is one of the best-known entrepreneurs and pioneers of the microcomputer revolution of the 1970s and 1980s. Born and raised in Seattle, Washington, Gates co-founded Microsoft with childhood friend Paul Allen in 1975, in Albuquerque, New Mexico; it went on to become the world's largest personal computer software company. Gates led the company as chairman and CEO until stepping down as CEO in January 2000, but he remained chairman and became chief software architect. During the late 1990s, Gates had been criticized for his business tactics, which have been considered anti-competitive. This opinion has been upheld by numerous court rulings. In June 2006, Gates announced that he would be transitioning to a part-time role at Microsoft and full-time work at the Bill & Melinda Gates Foundation, the private charitable foundation that he and his wife, Melinda Gates, established in 2000. He gradually transferred his duties to Ray Ozzie and Craig Mundie. He stepped down as chairman of Microsoft in February 2014 and assumed a new post as technology adviser to support the newly appointed CEO Satya Nadella."""]
ner_df = nlu.load('en.ner.onto.bert.cased_large').predict(text, output_level='chunk')
ner_df[["entities", "entities_class"]]
Results
+-----------------------+---------+
|chunk |ner_label|
+-----------------------+---------+
|William Henry Gates III|PERSON |
|October 28, 1955 |DATE |
|American |NORP |
|Microsoft Corporation |ORG |
|Microsoft |ORG |
|Gates |PERSON |
|May 2014 |DATE |
|one |CARDINAL |
|the 1970s |DATE |
|1980s |DATE |
|Seattle |GPE |
|Washington |GPE |
|Gates |PERSON |
|Microsoft |PERSON |
|Paul Allen |PERSON |
|1975 |DATE |
|Albuquerque |GPE |
|New Mexico |GPE |
|Gates |ORG |
|January 2000 |DATE |
+-----------------------+---------+
Model Information
| Model Name: | onto_bert_large_cased |
| Type: | ner |
| Compatibility: | Spark NLP 2.7.0+ |
| License: | Open Source |
| Edition: | Official |
| Input Labels: | [sentence, token, embeddings] |
| Output Labels: | [ner] |
| Language: | en |
Data Source
The model is trained based on data from OntoNotes 5.0
Benchmarking
Micro-average:
prec: 0.8947816, rec: 0.9059915, f1: 0.90035164
CoNLL Eval (test dataset):
processed 152728 tokens with 11257 phrases; found: 11351 phrases; correct: 10044.
accuracy: 98.02%; 10044 11257 11351 precision: 88.49%; recall: 89.22%; FB1: 88.85
CARDINAL: 793 935 953 precision: 83.21%; recall: 84.81%; FB1: 84.00 953
DATE: 1420 1602 1697 precision: 83.68%; recall: 88.64%; FB1: 86.09 1697
EVENT: 37 63 63 precision: 58.73%; recall: 58.73%; FB1: 58.73 63
FAC: 98 135 152 precision: 64.47%; recall: 72.59%; FB1: 68.29 152
GPE: 2128 2240 2218 precision: 95.94%; recall: 95.00%; FB1: 95.47 2218
LANGUAGE: 10 22 13 precision: 76.92%; recall: 45.45%; FB1: 57.14 13
LAW: 21 40 30 precision: 70.00%; recall: 52.50%; FB1: 60.00 30
LOC: 133 179 166 precision: 80.12%; recall: 74.30%; FB1: 77.10 166
MONEY: 279 314 317 precision: 88.01%; recall: 88.85%; FB1: 88.43 317
NORP: 796 841 840 precision: 94.76%; recall: 94.65%; FB1: 94.71 840
ORDINAL: 180 195 219 precision: 82.19%; recall: 92.31%; FB1: 86.96 219
ORG: 1620 1795 1873 precision: 86.49%; recall: 90.25%; FB1: 88.33 1873
PERCENT: 309 349 342 precision: 90.35%; recall: 88.54%; FB1: 89.44 342
PERSON: 1862 1988 1970 precision: 94.52%; recall: 93.66%; FB1: 94.09 1970
PRODUCT: 51 76 68 precision: 75.00%; recall: 67.11%; FB1: 70.83 68
QUANTITY: 81 105 99 precision: 81.82%; recall: 77.14%; FB1: 79.41 99
TIME: 116 212 179 precision: 64.80%; recall: 54.72%; FB1: 59.34 179
WORK_OF_ART: 110 166 152 precision: 72.37%; recall: 66.27%; FB1: 69.18 152
CoNLL Eval (development dataset):
processed 147724 tokens with 11066 phrases; found: 11259 phrases; correct: 10326.
accuracy: 98.73%; 10326 11066 11259 precision: 91.71%; recall: 93.31%; FB1: 92.51
CARDINAL: 869 938 1001 precision: 86.81%; recall: 92.64%; FB1: 89.63 1001
DATE: 1374 1507 1571 precision: 87.46%; recall: 91.17%; FB1: 89.28 1571
EVENT: 112 143 138 precision: 81.16%; recall: 78.32%; FB1: 79.72 138
FAC: 105 115 140 precision: 75.00%; recall: 91.30%; FB1: 82.35 140
GPE: 2213 2268 2293 precision: 96.51%; recall: 97.57%; FB1: 97.04 2293
LANGUAGE: 27 33 27 precision: 100.00%; recall: 81.82%; FB1: 90.00 27
LAW: 33 40 39 precision: 84.62%; recall: 82.50%; FB1: 83.54 39
LOC: 163 204 178 precision: 91.57%; recall: 79.90%; FB1: 85.34 178
MONEY: 257 274 275 precision: 93.45%; recall: 93.80%; FB1: 93.62 275
NORP: 806 847 841 precision: 95.84%; recall: 95.16%; FB1: 95.50 841
ORDINAL: 212 232 241 precision: 87.97%; recall: 91.38%; FB1: 89.64 241
ORG: 1618 1740 1771 precision: 91.36%; recall: 92.99%; FB1: 92.17 1771
PERCENT: 164 177 174 precision: 94.25%; recall: 92.66%; FB1: 93.45 174
PERSON: 1961 2020 2064 precision: 95.01%; recall: 97.08%; FB1: 96.03 2064
PRODUCT: 64 72 73 precision: 87.67%; recall: 88.89%; FB1: 88.28 73
QUANTITY: 83 100 96 precision: 86.46%; recall: 83.00%; FB1: 84.69 96
TIME: 165 214 203 precision: 81.28%; recall: 77.10%; FB1: 79.14 203
WORK_OF_ART: 100 142 134 precision: 74.63%; recall: 70.42%; FB1: 72.46 134