Triple

T6985033
Position Surface form Disambiguated ID Type / Status
Subject René Char E161939 entity
Predicate placeOfDeath P21 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: [René Char, placeOfDeath, Paris, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris, France
Context triple: [René Char, placeOfDeath, Paris, France]
  • 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 major Chilean department store and retail chain offering a wide range of apparel, home goods, and consumer products.
  • C. 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.
  • D. Parigi
    Parigi is a coastal town that serves as the administrative center of Parigi Moutong Regency in Central Sulawesi, Indonesia.
  • E. Parisi
    Parisi is an Italian surname most notably associated with Giorgio Parisi, a Nobel Prize–winning theoretical physicist known for his work on complex systems and statistical mechanics.
  • 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_69c68855dc0481909b4c7e9e9ed273db completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6db91fbc881908c26b7b991995062 completed March 27, 2026, 7:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7882e3cfc81909ca7ecf507ac9adc completed March 28, 2026, 7:50 a.m.
Created at: March 27, 2026, 2:31 p.m.