Triple

T15546124
Position Surface form Disambiguated ID Type / Status
Subject Émile Trélat E370613 entity
Predicate familyName P18 FINISHED
Object Trélat
Trélat is a French surname associated with several notable figures, including physicians, politicians, and academics.
 E1163007 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: Trélat | Statement: [Émile Trélat, familyName, Trélat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Trélat
Context triple: [Émile Trélat, familyName, Trélat]
  • A. Guichen
    Guichen was a French admiral, Luc Urbain de Bouëxic, comte de Guichen, noted for commanding French naval forces during the American Revolutionary War.
  • B. Mouriès
    Mouriès is a village in southern France’s Provence region, known for its olive oil production and location near the Alpilles hills.
  • C. Tôtes
    Tôtes is a small commune in the Seine-Maritime department of the Normandy region in northern France.
  • D. Fléron
    Fléron is a municipality in eastern Belgium located in the Walloon region’s Province of Liège.
  • E. Libatique
    Libatique is the surname of Matthew Libatique, an acclaimed American cinematographer known for his work on films such as "Black Swan" and "Requiem for a Dream."
  • 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: Trélat
Triple: [Émile Trélat, familyName, Trélat]
Generated description
Trélat is a French surname associated with several notable figures, including physicians, politicians, and academics.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Trélat
Target entity description: Trélat is a French surname associated with several notable figures, including physicians, politicians, and academics.
  • A. Guichen
    Guichen was a French admiral, Luc Urbain de Bouëxic, comte de Guichen, noted for commanding French naval forces during the American Revolutionary War.
  • B. Mouriès
    Mouriès is a village in southern France’s Provence region, known for its olive oil production and location near the Alpilles hills.
  • C. Tôtes
    Tôtes is a small commune in the Seine-Maritime department of the Normandy region in northern France.
  • D. Fléron
    Fléron is a municipality in eastern Belgium located in the Walloon region’s Province of Liège.
  • E. Libatique
    Libatique is the surname of Matthew Libatique, an acclaimed American cinematographer known for his work on films such as "Black Swan" and "Requiem for a Dream."
  • 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_69d85cc521a08190921fb50319dddc34 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04a9073948190b6e9cf504aacc7cf completed April 16, 2026, 2:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff455a38188190a593c70be09d6103 completed May 9, 2026, 2:31 p.m.
NEDg Description generation batch_69ff45dbc9dc8190b3cac64e4a418aa3 completed May 9, 2026, 2:34 p.m.
NED2 Entity disambiguation (via description) batch_69ff464571808190bfe7ef3a33d246f1 completed May 9, 2026, 2:35 p.m.
Created at: April 10, 2026, 4:07 a.m.