Triple

T18776306
Position Surface form Disambiguated ID Type / Status
Subject IAU Divisions E459142 entity
Predicate hasDivision P35 FINISHED
Object Division B: Facilities, Technologies and Data Science — NE NERFINISHED

How this triple was built (3 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Division B: Facilities, Technologies and Data Science | Statement: [IAU Divisions, hasDivision, Division B: Facilities, Technologies and Data Science]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Division B: Facilities, Technologies and Data Science
Context triple: [IAU Divisions, hasDivision, Division B: Facilities, Technologies and Data Science]
  • A. Office of Data Science
    The Office of Data Science is a specialized unit that applies advanced data analytics and quantitative methods to support the U.S. Securities and Exchange Commission’s economic, risk, and policy analysis.
  • B. Center for Data Engineering
    The Center for Data Engineering is a research hub at IIIT Hyderabad focused on advancing data science, big data systems, and machine learning technologies.
  • C. Intelligent Systems Division
    The Intelligent Systems Division is a research and development unit within Southwest Research Institute that focuses on advanced automation, artificial intelligence, and related intelligent technologies for industrial and governmental applications.
  • D. Resources and Technical Services Division
    The Resources and Technical Services Division was a former division of the American Library Association that focused on issues related to library collections, cataloging, and technical services.
  • E. Scientific Data Systems
    Scientific Data Systems was an early computer company known for producing advanced scientific and real-time computing systems in the 1960s before being acquired by Xerox.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Division B: Facilities, Technologies and Data Science
Target entity description: Division B: Facilities, Technologies and Data Science is an International Astronomical Union division focused on the development, coordination, and optimization of astronomical facilities, instrumentation, technologies, and data science practices for the global astronomy community.
  • A. Office of Data Science
    The Office of Data Science is a specialized unit that applies advanced data analytics and quantitative methods to support the U.S. Securities and Exchange Commission’s economic, risk, and policy analysis.
  • B. Center for Data Engineering
    The Center for Data Engineering is a research hub at IIIT Hyderabad focused on advancing data science, big data systems, and machine learning technologies.
  • C. Intelligent Systems Division
    The Intelligent Systems Division is a research and development unit within Southwest Research Institute that focuses on advanced automation, artificial intelligence, and related intelligent technologies for industrial and governmental applications.
  • D. Resources and Technical Services Division
    The Resources and Technical Services Division was a former division of the American Library Association that focused on issues related to library collections, cataloging, and technical services.
  • E. Scientific Data Systems
    Scientific Data Systems was an early computer company known for producing advanced scientific and real-time computing systems in the 1960s before being acquired by Xerox.
  • F. None of above. chosen

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8d396f54c8190ba49db31e8743842 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5933b912481908bfd97216eacb257 completed April 20, 2026, 2:45 a.m.
Created at: April 10, 2026, 11:52 a.m.