Triple

T11333770
Position Surface form Disambiguated ID Type / Status
Subject Charles de Noailles E268414 entity
Predicate placeOfDeath P21 FINISHED
Object Grasse, France E389045 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: Grasse, France | Statement: [Charles de Noailles, placeOfDeath, Grasse, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grasse, France
Context triple: [Charles de Noailles, placeOfDeath, Grasse, France]
  • A. Grasse chosen
    Grasse is a town in southeastern France renowned as the world’s perfume capital and a historic center of the fragrance industry.
  • B. Plascassier, Grasse, France
    Plascassier is a small village near Grasse in southeastern France, known for its picturesque Provençal setting and as the place where iconic French singer Édith Piaf died.
  • C. Fontenay-aux-Roses, France
    Fontenay-aux-Roses is a suburban commune in the southern outskirts of Paris, known for its residential character and proximity to major academic and research institutions.
  • D. Fontainebleau, France
    Fontainebleau, France is a historic town southeast of Paris best known for its vast forest and royal château, long associated with French monarchs and outdoor recreation.
  • E. Montreuil, France
    Montreuil is a suburban commune in the eastern part of the Paris metropolitan area, known for its diverse population and mix of residential, commercial, and cultural spaces.
  • 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_69d6aacb1f0881908c84a349fd1be047 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9fe5d5881908d786b212a554d8b completed April 9, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5263160548190adb7d5c0fd6af0e2 completed April 19, 2026, 7 p.m.
Created at: April 8, 2026, 9:33 p.m.