Triple

T3498162
Position Surface form Disambiguated ID Type / Status
Subject Alpes-Maritimes E73900 entity
Predicate containsCity P294 FINISHED
Object Puget-Théniers
Puget-Théniers is a small commune in southeastern France known for its picturesque setting in the Var valley and its historic Provençal village character.
 E362737 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: Puget-Théniers | Statement: [Alpes-Maritimes, containsCity, Puget-Théniers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Puget-Théniers
Context triple: [Alpes-Maritimes, containsCity, Puget-Théniers]
  • A. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • B. Breuillet
    Breuillet is a commune in the Essonne department in the Île-de-France region of northern France.
  • C. Maurepas
    Maurepas is a commune in the Yvelines department in the Île-de-France region of north-central France, known as a residential suburb southwest of Paris.
  • D. Montmorency
    Montmorency is a commune in the northern suburbs of Paris, France, known for its historic town center and surrounding Val-d'Oise area.
  • E. Boissière
    Boissière is a Paris Métro station on the city’s Right Bank, located in the 16th arrondissement near the Trocadéro area.
  • 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: Puget-Théniers
Triple: [Alpes-Maritimes, containsCity, Puget-Théniers]
Generated description
Puget-Théniers is a small commune in southeastern France known for its picturesque setting in the Var valley and its historic Provençal village character.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Puget-Théniers
Target entity description: Puget-Théniers is a small commune in southeastern France known for its picturesque setting in the Var valley and its historic Provençal village character.
  • A. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • B. Breuillet
    Breuillet is a commune in the Essonne department in the Île-de-France region of northern France.
  • C. Maurepas
    Maurepas is a commune in the Yvelines department in the Île-de-France region of north-central France, known as a residential suburb southwest of Paris.
  • D. Montmorency
    Montmorency is a commune in the northern suburbs of Paris, France, known for its historic town center and surrounding Val-d'Oise area.
  • E. Boissière
    Boissière is a Paris Métro station on the city’s Right Bank, located in the 16th arrondissement near the Trocadéro area.
  • 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_69ad85cdb6e48190a335d412b9194ed8 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbbd299ec8190b76b165b2fd70537 completed March 8, 2026, 6:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69b373d011c0819088245afe03be3c44 completed March 13, 2026, 2:17 a.m.
NEDg Description generation batch_69b3745c7304819085a47af79cd738c0 completed March 13, 2026, 2:20 a.m.
NED2 Entity disambiguation (via description) batch_69b374f5999c8190ae48570a412dc6dc completed March 13, 2026, 2:22 a.m.
Created at: March 8, 2026, 3:18 p.m.