Triple

T16102784
Position Surface form Disambiguated ID Type / Status
Subject Saint-Pierre-et-Saint-Paul church E390662 entity
Predicate locatedInGeographicalContext P3227 FINISHED
Object Alpine region of France 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: Alpine region of France | Statement: [Saint-Pierre-et-Saint-Paul church, locatedInGeographicalContext, Alpine region of France]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: locatedInGeographicalContext
Context triple: [Saint-Pierre-et-Saint-Paul church, locatedInGeographicalContext, Alpine region of France]
  • A. geographicContext chosen
    Indicates that one entity is situated within, associated with, or characterized by the geographic setting or region defined by another entity.
  • B. locatedInNationalContext
    Indicates that an entity exists or occurs within the geographical, political, or cultural boundaries of a specific nation.
  • C. likelyLocatedIn
    Indicates that an entity is probably situated within or associated with a particular location, though not with absolute certainty.
  • D. locatedIn
    Indicates that one entity exists or is situated within the spatial, administrative, or conceptual boundaries of another entity.
  • E. placesInContext
    Indicates that one entity situates, interprets, or frames another entity within a particular context or surrounding circumstances.
  • 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_69d87f1a8dd881909f1de6ef78849874 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e1ff6976ec8190b499e99b196b0285 completed April 17, 2026, 9:37 a.m.
PD Predicate disambiguation batch_69e182804208819087f35307cd6e4103 completed April 17, 2026, 12:44 a.m.
Created at: April 10, 2026, 5 a.m.