Triple

T10130851
Position Surface form Disambiguated ID Type / Status
Subject Jean-Michel E226333 entity
Predicate hasNotableBearer P458 FINISHED
Object Jean-Michel Damase
Jean-Michel Damase was a French composer and pianist known for his lyrical, neoclassical works, particularly for harp and chamber ensembles.
E842768 NE FINISHED

How this triple was built (4 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-Michel Damase | Statement: [Jean-Michel, hasNotableBearer, Jean-Michel Damase]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jean-Michel Damase
Context triple: [Jean-Michel, hasNotableBearer, Jean-Michel Damase]
  • A. Jean-Michel Defaye
    Jean-Michel Defaye is a French composer and trombonist known for his film scores and brass music, particularly for trombone.
  • B. Jean-Michel Raimond
    Jean-Michel Raimond is a French physicist known for his work in quantum optics and cavity quantum electrodynamics.
  • C. Jean-Michel Bernard
    Jean-Michel Bernard is a French composer and pianist known for his film scores and collaborations with director Michel Gondry.
  • D. Jean-Michel Remy
    Jean-Michel Remy is a French local politician serving as the mayor of the commune of Morlaincourt in northeastern France.
  • E. Patrice Dumas
    Patrice Dumas is a politically active Black student leader in the film "BlacKkKlansman," known for her passionate advocacy against racism and police brutality.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Jean-Michel Damase
Triple: [Jean-Michel, hasNotableBearer, Jean-Michel Damase]
Generated description
Jean-Michel Damase was a French composer and pianist known for his lyrical, neoclassical works, particularly for harp and chamber ensembles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jean-Michel Damase
Target entity description: Jean-Michel Damase was a French composer and pianist known for his lyrical, neoclassical works, particularly for harp and chamber ensembles.
  • A. Jean-Michel Defaye
    Jean-Michel Defaye is a French composer and trombonist known for his film scores and brass music, particularly for trombone.
  • B. Jean-Michel Raimond
    Jean-Michel Raimond is a French physicist known for his work in quantum optics and cavity quantum electrodynamics.
  • C. Jean-Michel Bernard
    Jean-Michel Bernard is a French composer and pianist known for his film scores and collaborations with director Michel Gondry.
  • D. Jean-Michel Remy
    Jean-Michel Remy is a French local politician serving as the mayor of the commune of Morlaincourt in northeastern France.
  • E. Patrice Dumas
    Patrice Dumas is a politically active Black student leader in the film "BlacKkKlansman," known for her passionate advocacy against racism and police brutality.
  • F. None of above. chosen

Provenance (5 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_69ca843057b48190a86730167f5d6b98 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cdd33438988190be45878f98695816 completed April 2, 2026, 2:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2cc7c50b08190a04aa2f58a6c300a completed April 5, 2026, 8:56 p.m.
NEDg Description generation batch_69d2cecd67448190a28a90148ad83c20 completed April 5, 2026, 9:06 p.m.
NED2 Entity disambiguation (via description) batch_69d2cf4d259881909f44bf1ec39524de completed April 5, 2026, 9:08 p.m.
Created at: March 30, 2026, 9:05 p.m.