Triple

T21608235
Position Surface form Disambiguated ID Type / Status
Subject Groupe de Puteaux E533232 entity
Predicate locatedNear P294 FINISHED
Object 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: Paris | Statement: [Groupe de Puteaux, locatedNear, Paris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris
Context triple: [Groupe de Puteaux, locatedNear, Paris]
  • A. Paris chosen
    Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
  • B. 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.
  • 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 was an enslaved man held in bondage by George Washington at the President's House in Philadelphia during his presidency.
  • 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_69e0c46411108190bba0d4176dffc9f3 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef17e7005c81908cfa86358b8dbef1 completed April 27, 2026, 8:01 a.m.
Created at: April 16, 2026, 6:33 p.m.