Triple

T36079937
Position Surface form Disambiguated ID Type / Status
Subject Gerland district E1043615 entity
Predicate hasFormerPrimaryUse P76363 FINISHED
Object chemical industry LITERAL 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: chemical industry | Statement: [Gerland district, hasFormerPrimaryUse, chemical industry]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasFormerPrimaryUse
Context triple: [Gerland district, hasFormerPrimaryUse, chemical industry]
  • A. hasFormerUse
    Indicates that something previously served a particular function or role that it no longer has.
  • B. hasPrimaryUseHistoric
    Indicates that something is primarily used for historic or heritage-related purposes.
  • C. hasUseOfFormerBase
    Indicates that an entity currently utilizes, occupies, or benefits from a location or facility that previously served as a base for another party or purpose.
  • D. formerPrimaryUse chosen
    Indicates that something was previously used as the main or principal function or purpose of an entity, but is no longer its current primary use.
  • E. hasFormerPrimaryTenant
    Indicates that an entity previously served as the main or principal tenant of another entity, but no longer holds that status.
  • F. None of above.

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_69f76e3154908190a6f702671c2bea08 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69fe7b1c506c8190869c1a22031e0571 completed May 9, 2026, 12:09 a.m.
PD Predicate disambiguation batch_69fe796b2bdc8190a86980d44008f875 completed May 9, 2026, 12:01 a.m.
Created at: May 3, 2026, 4:08 p.m.