Triple

T3488429
Position Surface form Disambiguated ID Type / Status
Subject OL postcode area E73664 entity
Predicate abbreviation P43 FINISHED
Object OL E73664 NE FINISHED

How this triple was built (2 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: OL | Statement: [OL postcode area, abbreviation, OL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OL
Context triple: [OL postcode area, abbreviation, OL]
  • A. OL chosen
    OL is a UK postcode area covering Oldham and surrounding parts of Greater Manchester and nearby regions in North West England.
  • B. OL
    OL is the commonly used abbreviation for Olympique Lyonnais, a major French football club best known internationally for its highly successful women's team.
  • C. OL
    OL is the vehicle registration code for the city of Oldenburg in the German state of Lower Saxony.
  • D. OLE
    OLE (Object Linking and Embedding) is a Microsoft technology that enables embedding and linking to documents and other objects within different applications, forming a foundation for later component technologies like ActiveX.
  • E. OLA
    OLA is the commonly used acronym for the United Nations Office of Legal Affairs, which provides legal advice and support to UN organs and specialized agencies.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ad85cca8d4819088494e9f3340fab5 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbb92b3ac8190b8675f5a5e9d4408 completed March 8, 2026, 6:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e6202ec81908c9614102e618fb5 completed March 13, 2026, 3:02 a.m.
Created at: March 8, 2026, 3:18 p.m.