Triple

T11067079
Position Surface form Disambiguated ID Type / Status
Subject Canal de l’Ourcq E261652 entity
Predicate owner P347 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: [Canal de l’Ourcq, owner, City of Paris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Paris
Context triple: [Canal de l’Ourcq, owner, City of Paris]
  • A. Parigi
    Parigi is a coastal town that serves as the administrative center of Parigi Moutong Regency in Central Sulawesi, Indonesia.
  • B. Paris chosen
    Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
  • C. Paris
    Paris is a major Chilean department store and retail chain offering a wide range of apparel, home goods, and consumer products.
  • D. Paris
    Paris is a budget-oriented AMD Sempron processor core designed for entry-level desktop computing.
  • E. Paris
    Paris is a prince of Troy in Greek mythology, best known for judging the beauty contest of the goddesses and for abducting Helen, which sparked the Trojan War.
  • 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_69d6aa98650481908609c7c56bfa7902 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79920428c81908db824ab54e08e8d completed April 9, 2026, 12:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69e441a5b5a481908a6fdf5f8e9bca8b completed April 19, 2026, 2:44 a.m.
Created at: April 8, 2026, 9:26 p.m.