DeepSData
Dataset guide · 机器学习与语料

Labelled data for fine tuning a geological Named Entity Recognition and Entity Relation Extraction model

This dataset consists of annotated sentences extracted from BGS memoirs, DECC/OGA onshore hydrocarbons well reports and Mineral Reconnaissance Programme (MRP) reports, for fine-tuning geological Named Entity Recognition and Entity Relation Extraction models.

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机器学习与语料Free to access

Key facts

InstitutionBritish Geological Survey (BGS)
CoverageUK geology (rock formations, geological ages, rock types, physical properties, locations)
Time spanPublished 2024
Scale3 files
LicenseLicense pending verification
AccessGitHub (BritishGeologicalSurvey/princeton-nlp-relation-extraction)

Contents & fields

The dataset is provided in JSONL format, containing sentences from BGS memoirs, DECC/OGA onshore well reports, and MRP reports, annotated with entities and relations. Entities include rock formations, geological ages, rock types, physical properties, and locations; relations include overlies and observedIn. Data exported from doccano annotation tool.

  • rock formations——rock formation entity
  • geological ages——geological age entity
  • rock types——rock type entity
  • physical properties——physical property entity
  • locations——location entity
  • overlies——relation: overlies
  • observedIn——relation: observed in

Research uses

Can be used to fine-tune pre-trained language models for automatic extraction of structured information from unstructured geological text, supporting geological modelling and subsurface characterisation.

This card was drafted from the source page; institution, coverage, time span, scale, fields and license are subject to the official page (pending human review).

Keywords

geologynamed entity recognitionrelation extractionlabelled dataNLPBritish Geological Survey

Access & license

License: License pending verification | Free to access

Why this is hard to get on your own

High-quality labelled geological data for NLP fine-tuning is scarce; this dataset provides a proof-of-concept annotated sample.

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