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Updated documentation #13556

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merged 32 commits into from
Feb 27, 2023
Merged

Updated documentation #13556

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37fd779
Added links to Python API
dcecchini Dec 13, 2022
e582a9d
Updated licensed utility and helpers docs
dcecchini Dec 16, 2022
7dd31a3
Added ModelTracer to utility and helper page
dcecchini Dec 19, 2022
7e03c19
Added AnnotationMerger page
dcecchini Dec 20, 2022
82ecf5e
Added BertSentenceChunkEmbeddings page
dcecchini Dec 20, 2022
d2ec1fa
Added ChunkMapper and ChunkConverter pages
dcecchini Dec 20, 2022
5e32cf8
Added DateNormalizer page
dcecchini Dec 20, 2022
e40b2d8
Added ChunkMapperFilterer page
dcecchini Dec 21, 2022
fc81ae8
Added ChunkMapperFilterer page
dcecchini Dec 21, 2022
16ddb57
Added Doc2ChunkInternal page
dcecchini Dec 21, 2022
2ce2937
Added DocumentHashCoder page
dcecchini Dec 21, 2022
9cf64ac
Added ZeroShotNerModel page
dcecchini Dec 21, 2022
c393529
Added ZeroShotRelationExtractionModel page
dcecchini Dec 21, 2022
02afabd
Fix Python API link for CoNLL dataset page
dcecchini Dec 21, 2022
dc4a8cc
Added ChunkMapperFilterer page
dcecchini Dec 22, 2022
d97aaeb
Added ChunkSentenceSplitter page
dcecchini Dec 22, 2022
733859e
Added ChunkSentenceSplitter page
dcecchini Dec 22, 2022
85d9dee
Added AssertionChunkConverter page
dcecchini Dec 22, 2022
76b9800
Add Python API link to license annotator template
dcecchini Dec 26, 2022
8e0299f
Added Risk Adjustments Score Calculation page
dcecchini Dec 26, 2022
04a516d
Merge branch 'master' into update-licensed-docs
C-K-Loan Jan 6, 2023
4fa2e2d
Merge branch 'master' into update-licensed-docs
maziyarpanahi Jan 12, 2023
55dcd31
Added missing parameters on Python code
dcecchini Jan 18, 2023
f9c240c
Added .vscode to gitignore
dcecchini Jan 18, 2023
5d4666e
Updated licensed annotators docs
dcecchini Jan 23, 2023
bfa32b5
Merge branch 'master' into update-licensed-docs
dcecchini Jan 24, 2023
f060821
Added ChunkEntityResolver page
dcecchini Jan 31, 2023
02d5cc3
Merge branch 'update-licensed-docs' of github.com:JohnSnowLabs/spark-…
dcecchini Jan 31, 2023
0d4cb0d
SentenceEntityResolver doesn't have ner_chunks as input
dcecchini Feb 23, 2023
6184d5d
Updated docstrings
dcecchini Feb 23, 2023
bedb529
Updated docs for SentenceEntityResolver
dcecchini Feb 23, 2023
d3c0680
Merge branch 'master' into update-licensed-docs
dcecchini Feb 27, 2023
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2 changes: 1 addition & 1 deletion docs/_posts/2020-11-27-sbiobertresolve_cpt_en.md
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Expand Up @@ -47,7 +47,7 @@ sbert_embedder = BertSentenceEmbeddings\
.setOutputCol("sbert_embeddings")

cpt_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_cpt","en", "clinical/models") \
.setInputCols(["ner_chunk", "sbert_embeddings"]) \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("resolution")\
.setDistanceFunction("EUCLIDEAN")

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2 changes: 1 addition & 1 deletion docs/_posts/2020-11-27-sbiobertresolve_icd10cm_en.md
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Expand Up @@ -47,7 +47,7 @@ sbert_embedder = BertSentenceEmbeddings\
.setOutputCol("sbert_embeddings")

icd10_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icd10cm","en", "clinical/models") \
.setInputCols(["ner_chunk", "sbert_embeddings"]) \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("resolution")\
.setDistanceFunction("EUCLIDEAN")

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2 changes: 1 addition & 1 deletion docs/_posts/2020-11-27-sbiobertresolve_icd10pcs_en.md
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Expand Up @@ -50,7 +50,7 @@ sbert_embedder = BertSentenceEmbeddings\
.setOutputCol("sbert_embeddings")

icd10pcs_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icd10pcs","en", "clinical/models") \
.setInputCols(["ner_chunk", "sbert_embeddings"]) \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("resolution")\
.setDistanceFunction("EUCLIDEAN")

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2 changes: 1 addition & 1 deletion docs/_posts/2020-11-27-sbiobertresolve_icdo_en.md
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Expand Up @@ -48,7 +48,7 @@ sbert_embedder = BertSentenceEmbeddings\
.setOutputCol("sbert_embeddings")

icdo_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icdo","en", "clinical/models") \
.setInputCols(["ner_chunk", "sbert_embeddings"]) \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("resolution")\
.setDistanceFunction("EUCLIDEAN")

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2 changes: 1 addition & 1 deletion docs/_posts/2020-11-27-sbiobertresolve_rxnorm_en.md
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Expand Up @@ -47,7 +47,7 @@ sbert_embedder = BertSentenceEmbeddings\
.setOutputCol("sbert_embeddings")

rxnorm_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_rxnorm","en", "clinical/models") \
.setInputCols(["ner_chunk", "sbert_embeddings"]) \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("resolution")\
.setDistanceFunction("EUCLIDEAN")

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2 changes: 1 addition & 1 deletion docs/_posts/2020-11-27-sbiobertresolve_snomed_auxConcepts_en.md
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Expand Up @@ -47,7 +47,7 @@ sbert_embedder = BertSentenceEmbeddings\
.setOutputCol("sbert_embeddings")

snomed_aux_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_snomed_auxConcepts","en", "clinical/models") \
.setInputCols(["ner_chunk", "sbert_embeddings"]) \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("resolution")\
.setDistanceFunction("EUCLIDEAN")

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2 changes: 1 addition & 1 deletion docs/_posts/2020-11-27-sbiobertresolve_snomed_auxConcepts_int_en.md
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Expand Up @@ -48,7 +48,7 @@ sbert_embedder = BertSentenceEmbeddings\
.setOutputCol("sbert_embeddings")

snomed_aux_int_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_snomed_auxConcepts_int","en", "clinical/models") \
.setInputCols(["ner_chunk", "sbert_embeddings"]) \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("resolution")\
.setDistanceFunction("EUCLIDEAN")

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2 changes: 1 addition & 1 deletion docs/_posts/2020-11-27-sbiobertresolve_snomed_findings_en.md
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Expand Up @@ -51,7 +51,7 @@ sbert_embedder = BertSentenceEmbeddings\
.setOutputCol("sbert_embeddings")

snomed_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_snomed_findings","en", "clinical/models") \
.setInputCols(["ner_chunk", "sbert_embeddings"]) \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("resolution")\
.setDistanceFunction("EUCLIDEAN")

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4 changes: 2 additions & 2 deletions docs/_posts/2020-12-13-sbiobertresolve_icd10cm_augmented_en.md
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Expand Up @@ -46,7 +46,7 @@ sbert_embedder = BertSentenceEmbeddings\
.setOutputCol("sbert_embeddings")

icd10_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icd10cm_augmented","en", "clinical/models") \
.setInputCols(["ner_chunk", "sbert_embeddings"]) \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("resolution")\
.setDistanceFunction("EUCLIDEAN")

Expand All @@ -68,7 +68,7 @@ val sbert_embedder = BertSentenceEmbeddings

val icd10_resolver = SentenceEntityResolverModel
.pretrained("sbiobertresolve_icd10cm_augmented","en", "clinical/models")
.setInputCols(Array("ner_chunk", "sbert_embeddings"))
.setInputCols(Array("sbert_embeddings"))
.setOutputCol("resolution")
.setDistanceFunction("EUCLIDEAN")

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6 changes: 3 additions & 3 deletions docs/_posts/Ahmetemintek/2021-12-24-sbiobertresolve_loinc_cased_en.md
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Expand Up @@ -72,7 +72,7 @@ sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli","en
.setCaseSensitive(True)

resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_loinc_cased", "en", "clinical/models") \
.setInputCols(["ner_chunk", "sbert_embeddings"])\
.setInputCols(["sbert_embeddings"])\
.setOutputCol("resolution")\
.setDistanceFunction("EUCLIDEAN")

Expand Down Expand Up @@ -129,8 +129,8 @@ val sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli"
.setCaseSensitive(True)

val resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_loinc_cased", "en", "clinical/models")
.setInputCols(Array("ner_chunk", "sbert_embeddings"))
.setOutputCol("resolution")
.setInputCols(Array("sbert_embeddings"))
.setOutputCol("resolution")\
.setDistanceFunction("EUCLIDEAN")

val pipeline = new Pipeline().setStages(Array(documentAssembler, sentenceDetector, tokenizer, word_embeddings, rad_ner, rad_ner_converter, chunk2doc, sbert_embedder, resolver))
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4 changes: 2 additions & 2 deletions .../Ahmetemintek/2022-02-26-sbiobertresolve_snomed_findings_aux_concepts_en_3_0.md
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Expand Up @@ -72,7 +72,7 @@ sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli","en
.setOutputCol("sbert_embeddings")

snomed_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_snomed_findings_aux_concepts", "en", "clinical/models") \
.setInputCols(["ner_chunk", "sbert_embeddings"]) \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("snomed_code")\
.setDistanceFunction("EUCLIDEAN")

Expand Down Expand Up @@ -128,7 +128,7 @@ val sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli"
.setOutputCol("sbert_embeddings")

val snomed_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_snomed_findings_aux_concepts", "en", "clinical/models")
.setInputCols(Array("ner_chunk", "sbert_embeddings"))
.setInputCols(Array("sbert_embeddings"))
.setOutputCol("snomed_code")

val new nlpPipeine().setStages(Array(documentAssembler,
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2 changes: 1 addition & 1 deletion docs/_posts/Ahmetemintek/2022-07-05-sbiobertresolve_umls_findings_en_3_0.md
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Expand Up @@ -72,7 +72,7 @@ sbert_embedder = BertSentenceEmbeddings\
.setOutputCol("sbert_embeddings")

resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_umls_findings","en", "clinical/models") \
.setInputCols(["ner_chunk_doc", "sbert_embeddings"]) \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("resolution")\
.setDistanceFunction("EUCLIDEAN")

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4 changes: 2 additions & 2 deletions docs/_posts/Ahmetemintek/2022-09-30-icd10_icd9_mapper_en.md
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Expand Up @@ -46,7 +46,7 @@ sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli", "e
.setOutputCol("sbert_embeddings")

icd_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icd10cm_augmented_billable_hcc", "en", "clinical/models") \
.setInputCols(["ner_chunk", "sbert_embeddings"]) \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("icd10cm_code")\
.setDistanceFunction("EUCLIDEAN")

Expand Down Expand Up @@ -80,7 +80,7 @@ val sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli"
.setOutputCol("sbert_embeddings")

val icd_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icd10cm_augmented_billable_hcc", "en", "clinical/models")
.setInputCols(Array("ner_chunk", "sbert_embeddings"))
.setInputCols(Array("sbert_embeddings"))
.setOutputCol("icd10cm_code")
.setDistanceFunction("EUCLIDEAN")

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4 changes: 2 additions & 2 deletions docs/_posts/Ahmetemintek/2022-10-12-sbiobertresolve_cvx_en.md
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Expand Up @@ -46,7 +46,7 @@ sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli", "e
.setOutputCol("sbert_embeddings")

cvx_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_cvx", "en", "clinical/models")\
.setInputCols(["ner_chunk", "sbert_embeddings"])\
.setInputCols(["sbert_embeddings"])\
.setOutputCol("cvx_code")\
.setDistanceFunction("EUCLIDEAN")

Expand All @@ -66,7 +66,7 @@ val sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli"
.setOutputCol("sbert_embeddings")

val cvx_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_cvx", "en", "clinical/models")
.setInputCols(Array("ner_chunk", "sbert_embeddings"))
.setInputCols(Array("sbert_embeddings"))
.setOutputCol("cvx_code")
.setDistanceFunction("EUCLIDEAN")

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4 changes: 2 additions & 2 deletions docs/_posts/Cabir40/2022-03-01-sbiobertresolve_atc_en_2_4.md
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Expand Up @@ -72,7 +72,7 @@ sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli", "e
.setCaseSensitive(False)

atc_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_atc", "en", "clinical/models")\
.setInputCols(["ner_chunk", "sentence_embeddings"]) \
.setInputCols(["sentence_embeddings"]) \
.setOutputCol("atc_code")\
.setDistanceFunction("EUCLIDEAN")

Expand Down Expand Up @@ -133,7 +133,7 @@ val sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli"
.setCaseSensitive(False)

val atc_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_atc", "en", "clinical/models")
.setInputCols(Array("ner_chunk", "sentence_embeddings"))
.setInputCols(Array("sentence_embeddings"))
.setOutputCol("atc_code")
.setDistanceFunction("EUCLIDEAN")

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4 changes: 2 additions & 2 deletions docs/_posts/Cabir40/2022-03-01-sbiobertresolve_atc_en_3_0.md
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Expand Up @@ -72,7 +72,7 @@ sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli", "e
.setCaseSensitive(False)

atc_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_atc", "en", "clinical/models")\
.setInputCols(["ner_chunk", "sentence_embeddings"]) \
.setInputCols(["sentence_embeddings"]) \
.setOutputCol("atc_code")\
.setDistanceFunction("EUCLIDEAN")

Expand Down Expand Up @@ -133,7 +133,7 @@ val sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli"
.setCaseSensitive(False)

val atc_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_atc", "en", "clinical/models")
.setInputCols(Array("ner_chunk", "sentence_embeddings"))
.setInputCols(Array("sentence_embeddings"))
.setOutputCol("atc_code")
.setDistanceFunction("EUCLIDEAN")

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4 changes: 2 additions & 2 deletions docs/_posts/Cabir40/2022-04-25-sbiobertresolve_rxnorm_action_treatment_en_2_4.md
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Expand Up @@ -46,7 +46,7 @@ sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli", "e
.setOutputCol("sbert_embeddings")

rxnorm_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_rxnorm_action_treatment", "en", "clinical/models")\
.setInputCols(["ner_chunk", "sbert_embeddings"])\
.setInputCols(["sbert_embeddings"])\
.setOutputCol("rxnorm_code")\
.setDistanceFunction("EUCLIDEAN")

Expand All @@ -66,7 +66,7 @@ val sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli"
.setOutputCol("sbert_embeddings")

val rxnorm_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_rxnorm_action_treatment", "en", "clinical/models")
.setInputCols(Array("ner_chunk", "sbert_embeddings"))
.setInputCols(Array("sbert_embeddings"))
.setOutputCol("rxnorm_code")
.setDistanceFunction("EUCLIDEAN")

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4 changes: 2 additions & 2 deletions docs/_posts/Cabir40/2022-05-11-sbiobertresolve_icd10cm_slim_billable_hcc_en_3_0.md
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Expand Up @@ -85,7 +85,7 @@ sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli", "e
.setCaseSensitive(False)

icd_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icd10cm_slim_billable_hcc", "en", "clinical/models") \
.setInputCols(["ner_chunk", "sentence_embeddings"]) \
.setInputCols(["sentence_embeddings"]) \
.setOutputCol("icd_code")\
.setDistanceFunction("EUCLIDEAN")

Expand Down Expand Up @@ -149,7 +149,7 @@ val sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli"
.setCaseSensitive(False)

val resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icd10cm_slim_billable_hcc", "en", "clinical/models")
.setInputCols(Array("ner_chunk", "sentence_embeddings"))
.setInputCols(Array("sentence_embeddings"))
.setOutputCol("icd_code")
.setDistanceFunction("EUCLIDEAN")

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4 changes: 2 additions & 2 deletions docs/_posts/Cabir40/2022-05-12-sbiobertresolve_icd10cm_slim_normalized_en_3_0.md
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Expand Up @@ -86,7 +86,7 @@ sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli", "e
.setCaseSensitive(False)

icd_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icd10cm_slim_normalized", "en", "clinical/models") \
.setInputCols(["ner_chunk", "sentence_embeddings"]) \
.setInputCols(["sentence_embeddings"]) \
.setOutputCol("icd_code")\
.setDistanceFunction("EUCLIDEAN")\
.setReturnCosineDistances(True)
Expand Down Expand Up @@ -151,7 +151,7 @@ val sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli"
.setCaseSensitive(False)

val resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icd10cm_slim_normalized", "en", "clinical/models")
.setInputCols(Array("ner_chunk", "sentence_embeddings"))
.setInputCols(Array("sentence_embeddings"))
.setOutputCol("icd_code")
.setDistanceFunction("EUCLIDEAN")
.setReturnCosineDistances(True)
Expand Down
5 changes: 2 additions & 3 deletions docs/_posts/Damla-Gurbaz/2022-06-26-icd10cm_snomed_mapper_en_3_0.md
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Expand Up @@ -47,7 +47,7 @@ sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli", "e
.setOutputCol("sbert_embeddings")

icd_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icd10cm_augmented_billable_hcc", "en", "clinical/models") \
.setInputCols(["ner_chunk", "sbert_embeddings"]) \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("icd10cm_code")\
.setDistanceFunction("EUCLIDEAN")

Expand Down Expand Up @@ -79,7 +79,7 @@ val sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli"
.setOutputCol("sbert_embeddings")

val icd_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icd10cm_augmented_billable_hcc", "en", "clinical/models")
.setInputCols(Array("ner_chunk", "sbert_embeddings"))
.setInputCols(Array("sbert_embeddings"))
.setOutputCol("icd10cm_code")
.setDistanceFunction("EUCLIDEAN")

Expand Down Expand Up @@ -131,4 +131,3 @@ nlu.load("en.icd10cm_to_snomed").predict("""Diabetes Mellitus""")
|Output Labels:|[mappings]|
|Language:|en|
|Size:|1.1 MB|

4 changes: 2 additions & 2 deletions docs/_posts/Damla-Gurbaz/2022-06-26-snomed_icd10cm_mapper_en_3_0.md
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Expand Up @@ -46,7 +46,7 @@ sbert_embedder = BertSentenceEmbeddings.pretrained("sbert_jsl_medium_uncased", "
.setOutputCol("sbert_embeddings")

snomed_resolver = SentenceEntityResolverModel.pretrained("sbertresolve_snomed_conditions", "en", "clinical/models") \
.setInputCols(["ner_chunk", "sbert_embeddings"]) \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("snomed_code")\
.setDistanceFunction("EUCLIDEAN")

Expand Down Expand Up @@ -79,7 +79,7 @@ val sbert_embedder = BertSentenceEmbeddings.pretrained("sbert_jsl_medium_uncased
.setOutputCol("sbert_embeddings")

val snomed_resolver = SentenceEntityResolverModel.pretrained("sbertresolve_snomed_conditions", "en", "clinical/models")
.setInputCols(Array("ner_chunk", "sbert_embeddings"))
.setInputCols(Array("sbert_embeddings"))
.setOutputCol("snomed_code")
.setDistanceFunction("EUCLIDEAN")

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4 changes: 2 additions & 2 deletions docs/_posts/HashamUlHaq/2021-04-29-sbiobertresolve_loinc_en.md
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Expand Up @@ -75,7 +75,7 @@ sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli","en
.setOutputCol("sbert_embeddings")

resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_loinc","en", "clinical/models") \
.setInputCols(["ner_chunk", "sbert_embeddings"]) \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("resolution")\
.setDistanceFunction("EUCLIDEAN")

Expand Down Expand Up @@ -125,7 +125,7 @@ val sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli"
.setOutputCol("sbert_embeddings")

val resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_loinc","en", "clinical/models")
.setInputCols(Array("ner_chunk", "sbert_embeddings"))
.setInputCols(Array("sbert_embeddings"))
.setOutputCol("resolution")
.setDistanceFunction("EUCLIDEAN")

Expand Down
2 changes: 1 addition & 1 deletion docs/_posts/HashamUlHaq/2021-04-29-sbluebertresolve_loinc_en.md
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Expand Up @@ -45,7 +45,7 @@ sbert_embedder = BertSentenceEmbeddings\
.setOutputCol("sbert_embeddings")

resolver = SentenceEntityResolverModel.pretrained("sbluebertresolve_loinc","en", "clinical/models") \
.setInputCols(["ner_chunk", "sbert_embeddings"]) \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("resolution")\
.setDistanceFunction("EUCLIDEAN")

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4 changes: 2 additions & 2 deletions docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icd10cm_augmented_en.md
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Expand Up @@ -71,7 +71,7 @@ sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli","en
.setOutputCol("sbert_embeddings")

icd10_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icd10cm_augmented","en", "clinical/models") \
.setInputCols(["ner_chunk", "sbert_embeddings"]) \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("resolution")\
.setDistanceFunction("EUCLIDEAN")

Expand Down Expand Up @@ -115,7 +115,7 @@ val sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli"
.setOutputCol("sbert_embeddings")

val icd10_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icd10cm_augmented","en", "clinical/models")
.setInputCols(Array("ner_chunk", "sbert_embeddings"))
.setInputCols(Array("sbert_embeddings"))
.setOutputCol("resolution")
.setDistanceFunction("EUCLIDEAN")

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4 changes: 2 additions & 2 deletions docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icd10cm_en.md
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Original file line number Diff line number Diff line change
Expand Up @@ -71,7 +71,7 @@ sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli","en
.setOutputCol("sbert_embeddings")

icd10_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icd10cm","en", "clinical/models") \
.setInputCols(["entities", "sbert_embeddings"]) \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("resolution")\
.setDistanceFunction("EUCLIDEAN")

Expand Down Expand Up @@ -115,7 +115,7 @@ val sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli"
.setOutputCol("sbert_embeddings")

val icd10_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icd10cm","en", "clinical/models")
.setInputCols(Array("entities", "sbert_embeddings"))
.setInputCols(Array("sbert_embeddings"))
.setOutputCol("resolution")
.setDistanceFunction("EUCLIDEAN")

Expand Down
4 changes: 2 additions & 2 deletions docs/_posts/HashamUlHaq/2021-05-16-sbiobertresolve_icdo_en.md
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Original file line number Diff line number Diff line change
Expand Up @@ -73,7 +73,7 @@ sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli","en
.setOutputCol("sbert_embeddings")

icdo_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icdo","en", "clinical/models")\
.setInputCols(["ner_chunk", "sbert_embeddings"]) \
.setInputCols(["sbert_embeddings"]) \
.setOutputCol("resolution")\
.setDistanceFunction("EUCLIDEAN")

Expand Down Expand Up @@ -117,7 +117,7 @@ val sbert_embedder = BertSentenceEmbeddings.pretrained("sbiobert_base_cased_mli"
.setOutputCol("sbert_embeddings")

val icdo_resolver = SentenceEntityResolverModel.pretrained("sbiobertresolve_icdo","en", "clinical/models")
.setInputCols(Array("ner_chunk", "sbert_embeddings"))
.setInputCols(Array("sbert_embeddings"))
.setOutputCol("resolution")
.setDistanceFunction("EUCLIDEAN")

Expand Down
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