Triple

T21788989
Position Surface form Disambiguated ID Type / Status
Subject Corentin-Urbain Leissègues E537916 entity
Predicate familyName P18 FINISHED
Object Leissègues
Leissègues is a French surname most notably borne by Corentin-Urbain Leissègues, a French naval officer active during the late 18th and early 19th centuries.
E1503063 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: Leissègues | Statement: [Corentin-Urbain Leissègues, familyName, Leissègues]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leissègues
Context triple: [Corentin-Urbain Leissègues, familyName, Leissègues]
  • A. Valiergues
    Valiergues is a small commune in the Corrèze department of central France.
  • B. Olliergues
    Olliergues is a small commune in central France’s Puy-de-Dôme department, known for its rural setting in the Auvergne region.
  • C. Sivergues
    Sivergues is a small rural commune in southeastern France, known for its remote, picturesque setting in the Luberon region.
  • D. Bessèges
    Bessèges is a commune in the Gard department of southern France, historically known for its coal mining and location in the Cévennes region.
  • E. Rigny-Ussé
    Rigny-Ussé is a small commune in central France best known for hosting the fairy-tale Château d’Ussé, said to have inspired Charles Perrault’s “Sleeping Beauty.”
  • 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: Leissègues
Triple: [Corentin-Urbain Leissègues, familyName, Leissègues]
Generated description
Leissègues is a French surname most notably borne by Corentin-Urbain Leissègues, a French naval officer active during the late 18th and early 19th centuries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Leissègues
Target entity description: Leissègues is a French surname most notably borne by Corentin-Urbain Leissègues, a French naval officer active during the late 18th and early 19th centuries.
  • A. Valiergues
    Valiergues is a small commune in the Corrèze department of central France.
  • B. Olliergues
    Olliergues is a small commune in central France’s Puy-de-Dôme department, known for its rural setting in the Auvergne region.
  • C. Sivergues
    Sivergues is a small rural commune in southeastern France, known for its remote, picturesque setting in the Luberon region.
  • D. Bessèges
    Bessèges is a commune in the Gard department of southern France, historically known for its coal mining and location in the Cévennes region.
  • E. Rigny-Ussé
    Rigny-Ussé is a small commune in central France best known for hosting the fairy-tale Château d’Ussé, said to have inspired Charles Perrault’s “Sleeping Beauty.”
  • 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_69e0c47198f881908cb0d237266c10e9 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f0621dfa3c8190921bfccbff7331f2 completed April 28, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0a3e72ff48819092b5748718550120 completed May 17, 2026, 10:17 p.m.
NEDg Description generation batch_6a0a3fa18b8481909b0a0471bc4eb592 completed May 17, 2026, 10:22 p.m.
NED2 Entity disambiguation (via description) batch_6a0a405450a0819089794cc07aa291b8 completed May 17, 2026, 10:25 p.m.
Created at: April 16, 2026, 6:52 p.m.