Triple

T19676204
Position Surface form Disambiguated ID Type / Status
Subject Monuments historiques of Paris E472458 entity
Predicate appliesToJurisdiction P82 FINISHED
Object City of Paris NE NERFINISHED

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: City of Paris | Statement: [Monuments historiques of Paris, appliesToJurisdiction, City of Paris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Paris
Context triple: [Monuments historiques of Paris, appliesToJurisdiction, City of Paris]
  • A. Ville de Paris
    Ville de Paris was a prominent French ship of the line, originally the flagship of Admiral de Grasse, that played a central role in major naval engagements during the American Revolutionary War.
  • B. Ville de Paris chosen
    Ville de Paris is the municipal government and administrative authority responsible for managing and providing public services in the city of Paris, France.
  • C. Parigi
    Parigi is a town located in the Vikarabad district of the Indian state of Telangana.
  • D. Parigi
    Parigi is a coastal town that serves as the administrative center of Parigi Moutong Regency in Central Sulawesi, Indonesia.
  • E. Paris
    Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e514f2e08190ba70a4449519d218 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e641bbea8c8190b0ad841d95068e0e completed April 20, 2026, 3:09 p.m.
Created at: April 10, 2026, 1:45 p.m.