Triple

T821789
Position Surface form Disambiguated ID Type / Status
Subject Mike Thibault E17763 entity
Predicate familyName P18 FINISHED
Object Thibault
Thibault is a surname most notably associated with Mike Thibault, a prominent American basketball coach in the WNBA.
 E126701 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: Thibault | Statement: [Mike Thibault, familyName, Thibault]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Thibault
Context triple: [Mike Thibault, familyName, Thibault]
  • A. Laurent
    Laurent is a Belgian prince, the younger son of King Albert II and Queen Paola, known for his environmental interests and occasional public controversies.
  • B. Pierre
    Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
  • C. Théodore
    Théodore is a masculine given name of Greek origin, commonly used in French-speaking countries and borne by notable figures such as the Reformation theologian Théodore Beza.
  • D. Hilaire
    Hilaire is a given name associated with the French Impressionist artist Edgar Degas, whose full name was Hilaire-Germain-Edgar Degas.
  • E. Antoine
    Antoine is the given name of Antoine de la Mothe Cadillac, the French explorer and founder of Detroit.
  • 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: Thibault
Triple: [Mike Thibault, familyName, Thibault]
Generated description
Thibault is a surname most notably associated with Mike Thibault, a prominent American basketball coach in the WNBA.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Thibault
Target entity description: Thibault is a surname most notably associated with Mike Thibault, a prominent American basketball coach in the WNBA.
  • A. Laurent
    Laurent is a Belgian prince, the younger son of King Albert II and Queen Paola, known for his environmental interests and occasional public controversies.
  • B. Pierre
    Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
  • C. Théodore
    Théodore is a masculine given name of Greek origin, commonly used in French-speaking countries and borne by notable figures such as the Reformation theologian Théodore Beza.
  • D. Hilaire
    Hilaire is a given name associated with the French Impressionist artist Edgar Degas, whose full name was Hilaire-Germain-Edgar Degas.
  • E. Antoine
    Antoine is the given name of Antoine de la Mothe Cadillac, the French explorer and founder of Detroit.
  • 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_69a4937bcaac8190a322524ac6f45a5a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab7aea38819092a0860ec6e2a033 completed March 1, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4bfac5cc8190a5fba1c5da98391d completed March 7, 2026, 4:02 p.m.
NEDg Description generation batch_69ac4d1d58ac8190b1fc39a28aff8c46 completed March 7, 2026, 4:06 p.m.
NED2 Entity disambiguation (via description) batch_69ac4d90c3dc819092f6be4888851477 completed March 7, 2026, 4:08 p.m.
Created at: March 1, 2026, 7:38 p.m.