Triple

T10790937
Position Surface form Disambiguated ID Type / Status
Subject Jacques Demy E254574 entity
Predicate workLocation P7 FINISHED
Object Paris, France 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: Paris, France | Statement: [Jacques Demy, workLocation, Paris, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris, France
Context triple: [Jacques Demy, workLocation, Paris, France]
  • A. Paris region, France
    The Paris region in France, also known as Île-de-France, is the country’s most populous and economically significant area, centered around the capital city of Paris and encompassing its surrounding suburbs and satellite towns.
  • 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_69d6aa609f008190a294200aefcb7bd5 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d732f5b8248190a633dc44ae620a3a completed April 9, 2026, 5:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69de84a63de0819085f1e982c8348811 completed April 14, 2026, 6:17 p.m.
Created at: April 8, 2026, 9:17 p.m.