Triple

T2626623
Position Surface form Disambiguated ID Type / Status
Subject Fannette Island E59132 entity
Predicate hasRuins P32402 FINISHED
Object stone teahouse 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: stone teahouse | Statement: [Fannette Island, hasRuins, stone teahouse]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasRuins
Context triple: [Fannette Island, hasRuins, stone teahouse]
  • A. hasRuin chosen
    Indicates that one entity possesses, contains, or is associated with a ruin or ruined structure.
  • B. hasCauseOfDestruction
    Indicates that one entity is the cause or agent responsible for the destruction or damage of another entity.
  • C. hasDemolitionOrDestruction
    Indicates that one entity causes, undergoes, or is associated with the demolition or destruction of another entity.
  • D. hasArchaeologicalFeature
    Indicates that an entity possesses, contains, or is associated with a specific archaeological feature or structure.
  • E. sufferedDestructionIn
    Indicates that an entity experienced damage, ruin, or devastation during or as part of a specified event or period.
  • 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_69ab4ac558388190962492cd2e1b0ce6 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abdb0e7b888190bfa5d2e33f00ec0f completed March 7, 2026, 8 a.m.
PD Predicate disambiguation batch_69abd810d7f481908e81c305772c4c14 completed March 7, 2026, 7:47 a.m.
Created at: March 6, 2026, 9:50 p.m.