Triple

T14793485
Position Surface form Disambiguated ID Type / Status
Subject Council of Paris E347714 entity
Predicate jurisdiction P82 FINISHED
Object City of Paris E568 NE 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: City of Paris | Statement: [Council of Paris, jurisdiction, City of Paris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Paris
Context triple: [Council of Paris, jurisdiction, 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. Parigi
    Parigi is a coastal town that serves as the administrative center of Parigi Moutong Regency in Central Sulawesi, Indonesia.
  • C. Paris chosen
    Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
  • D. Paris
    Paris is a major Chilean department store and retail chain offering a wide range of apparel, home goods, and consumer products.
  • E. Paris
    Paris is a budget-oriented AMD Sempron processor core designed for entry-level desktop computing.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d822ea8b7c819097dfadf3d45545e6 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decd5ec43c8190ad7a10a556519bb0 completed April 14, 2026, 11:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe7e7bb24c8190b67fb4e098b15d83 completed May 9, 2026, 12:23 a.m.
Created at: April 10, 2026, 1:31 a.m.