Triple

T717293
Position Surface form Disambiguated ID Type / Status
Subject Occitanie E14341 entity
Predicate containsCity P294 FINISHED
Object Lunel
Lunel is a commune in southern France known for its historic center and location between Montpellier and Nîmes in the Occitanie region.
 E161071 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: Lunel | Statement: [Occitanie, containsCity, Lunel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lunel
Context triple: [Occitanie, containsCity, Lunel]
  • A. Blaye
    Blaye is a wine-producing area on the right bank of the Gironde estuary in southwestern France, known for its red and white Bordeaux wines and historic citadel.
  • B. Aigues-Mortes
    Aigues-Mortes is a historic fortified town in southern France, renowned for its well-preserved medieval walls and proximity to the salt marshes of the Camargue.
  • C. Frontignan
    Frontignan is a coastal commune in southern France known for its Muscat wine production and Mediterranean setting near Sète.
  • D. Sète
    Sète is a coastal port city in southern France known for its canals, fishing industry, and vibrant maritime culture on the Mediterranean Sea.
  • E. Nîmes
    Nîmes is a historic city in southern France renowned for its well-preserved Roman monuments, including the Arena of Nîmes and the Maison Carrée.
  • 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: Lunel
Triple: [Occitanie, containsCity, Lunel]
Generated description
Lunel is a commune in southern France known for its historic center and location between Montpellier and Nîmes in the Occitanie region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lunel
Target entity description: Lunel is a commune in southern France known for its historic center and location between Montpellier and Nîmes in the Occitanie region.
  • A. Blaye
    Blaye is a wine-producing area on the right bank of the Gironde estuary in southwestern France, known for its red and white Bordeaux wines and historic citadel.
  • B. Aigues-Mortes
    Aigues-Mortes is a historic fortified town in southern France, renowned for its well-preserved medieval walls and proximity to the salt marshes of the Camargue.
  • C. Frontignan
    Frontignan is a coastal commune in southern France known for its Muscat wine production and Mediterranean setting near Sète.
  • D. Sète
    Sète is a coastal port city in southern France known for its canals, fishing industry, and vibrant maritime culture on the Mediterranean Sea.
  • E. Nîmes
    Nîmes is a historic city in southern France renowned for its well-preserved Roman monuments, including the Arena of Nîmes and the Maison Carrée.
  • 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_69a4934a36e081909e7abef98b898a4e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a577658881909c12951d63d96377 completed March 1, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69ace5371c2c8190861a5cbf9d089e4f completed March 8, 2026, 2:55 a.m.
NEDg Description generation batch_69ace5db553c8190b0d09462411f3dcf completed March 8, 2026, 2:58 a.m.
NED2 Entity disambiguation (via description) batch_69ace647c04881908ab550505110c29b completed March 8, 2026, 3 a.m.
Created at: March 1, 2026, 7:37 p.m.