Triple

T3931065
Position Surface form Disambiguated ID Type / Status
Subject Tarn-et-Garonne E90794 entity
Predicate contains P35 FINISHED
Object Lauzerte
Lauzerte is a medieval hilltop village in southern France known for its well-preserved historic center and picturesque views over the surrounding countryside.
 E400992 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: Lauzerte | Statement: [Tarn-et-Garonne, contains, Lauzerte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lauzerte
Context triple: [Tarn-et-Garonne, contains, Lauzerte]
  • A. Lalumière
    Lalumière is a French surname most notably borne by Catherine Lalumière, a prominent French politician and former European Parliament member.
  • B. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • C. Gressy
    Gressy is a small French commune located in the Île-de-France region, known for its residential character and proximity to Paris and Charles de Gaulle Airport.
  • D. Boissière
    Boissière is a Paris Métro station on the city’s Right Bank, located in the 16th arrondissement near the Trocadéro area.
  • E. Valleiry
    Valleiry is a small French commune in the Haute-Savoie department of the Auvergne-Rhône-Alpes region in southeastern France, near the Swiss border.
  • 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: Lauzerte
Triple: [Tarn-et-Garonne, contains, Lauzerte]
Generated description
Lauzerte is a medieval hilltop village in southern France known for its well-preserved historic center and picturesque views over the surrounding countryside.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lauzerte
Target entity description: Lauzerte is a medieval hilltop village in southern France known for its well-preserved historic center and picturesque views over the surrounding countryside.
  • A. Lalumière
    Lalumière is a French surname most notably borne by Catherine Lalumière, a prominent French politician and former European Parliament member.
  • B. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • C. Gressy
    Gressy is a small French commune located in the Île-de-France region, known for its residential character and proximity to Paris and Charles de Gaulle Airport.
  • D. Boissière
    Boissière is a Paris Métro station on the city’s Right Bank, located in the 16th arrondissement near the Trocadéro area.
  • E. Valleiry
    Valleiry is a small French commune in the Haute-Savoie department of the Auvergne-Rhône-Alpes region in southeastern France, near the Swiss border.
  • 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_69aed95f26e0819094b0e71974543a19 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeeda98058819094dd6ab223670860 completed March 9, 2026, 3:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5338afa348190bc5ac0b0319c6e45 completed March 14, 2026, 10:08 a.m.
NEDg Description generation batch_69b53404294881908a91dced77133b57 completed March 14, 2026, 10:10 a.m.
NED2 Entity disambiguation (via description) batch_69b53482a40c8190bd62b0bc8df92c0c completed March 14, 2026, 10:12 a.m.
Created at: March 9, 2026, 3:23 p.m.