Triple

T19175562
Position Surface form Disambiguated ID Type / Status
Subject Camp Fire E469427 entity
Predicate destroyedBusinesses P112414 FINISHED
Object over 500 commercial buildings 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: over 500 commercial buildings | Statement: [Camp Fire, destroyedBusinesses, over 500 commercial buildings]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: destroyedBusinesses
Context triple: [Camp Fire, destroyedBusinesses, over 500 commercial buildings]
  • A. numberOfBusinessesDestroyed chosen
    Indicates the quantity of businesses that have been destroyed in a given event or context.
  • B. demolishedOrDestroyed
    Indicates that one entity has caused another entity to be torn down, ruined, or rendered unusable, typically through deliberate demolition or destructive force.
  • C. businessBase
    Indicates that one entity serves as the primary business foundation, core location, or main operational base for another entity.
  • D. demolished
    Indicates that one entity completely destroyed or razed another entity, typically a structure or object, so that it no longer exists in its previous form.
  • E. previousBuildingDemolished
    Indicates that a building which previously occupied the same site or fulfilled the same role has been demolished.
  • 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_69d8dd09d5a081909ae43c286651ae5a completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5f166d3888190adaf6dc8531a8ed1 completed April 20, 2026, 9:27 a.m.
PD Predicate disambiguation batch_69e4b9bb158481909478ca2e06f3ba39 completed April 19, 2026, 11:17 a.m.
Created at: April 10, 2026, 12:06 p.m.