Triple

T11641450
Position Surface form Disambiguated ID Type / Status
Subject Montparnasse Cemetery E276669 entity
Predicate burialPlaceOf P196 FINISHED
Object Jean Carmet E663444 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: Jean Carmet | Statement: [Montparnasse Cemetery, burialPlaceOf, Jean Carmet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jean Carmet
Context triple: [Montparnasse Cemetery, burialPlaceOf, Jean Carmet]
  • A. Jean Carmet chosen
    Jean Carmet was a renowned French character actor celebrated for his prolific film career and his blend of comic and dramatic roles.
  • B. Jacques Fath
    Jacques Fath was a prominent mid-20th-century French fashion designer known for his glamorous, innovative couture that helped shape postwar Parisian style.
  • C. Pierre Cartier
    Pierre Cartier was a prominent French jeweler and member of the Cartier family who played a key role in popularizing exceptional gemstones and luxury jewelry in the early 20th century.
  • D. Pierre Cartier
    Pierre Cartier is a French mathematician known for his influential work in algebra, number theory, and representation theory, as well as for his role in shaping modern mathematics through the Bourbaki movement.
  • E. Frank Ricard
    Frank Ricard is a hard-partying, middle-aged man whose attempts to relive his college days become a central source of comedy and chaos in the film "Old School."
  • 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_69d6aafbb3c081908a9cdb4ecb8d981d completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a260ab488190ab1c00d9850f3096 completed April 10, 2026, 7:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ee87deb3888190842bd61efd7b3989 completed April 26, 2026, 9:47 p.m.
Created at: April 8, 2026, 9:39 p.m.