Triple

T3173418
Position Surface form Disambiguated ID Type / Status
Subject Paris Métro Line 6 E66406 entity
Predicate servesStation P839 FINISHED
Object Boissière
Boissière is a Paris Métro station on the city’s Right Bank, located in the 16th arrondissement near the Trocadéro area.
 E336072 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: Boissière | Statement: [Paris Métro Line 6, servesStation, Boissière]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Boissière
Context triple: [Paris Métro Line 6, servesStation, Boissière]
  • A. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • B. 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.
  • C. Pélissier
    Pélissier is a French surname borne by various notable figures, including military leaders, athletes, and artists.
  • D. Vautrin
    Vautrin is a cunning, charismatic criminal mastermind and recurring antihero in Honoré de Balzac’s La Comédie humaine, known for his manipulative intelligence and complex moral ambiguity.
  • E. Confignon
    Confignon is a small municipality in the canton of Geneva in southwestern Switzerland, known for its residential character and proximity to the city of Geneva.
  • 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: Boissière
Triple: [Paris Métro Line 6, servesStation, Boissière]
Generated description
Boissière is a Paris Métro station on the city’s Right Bank, located in the 16th arrondissement near the Trocadéro area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Boissière
Target entity description: Boissière is a Paris Métro station on the city’s Right Bank, located in the 16th arrondissement near the Trocadéro area.
  • A. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • B. 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.
  • C. Pélissier
    Pélissier is a French surname borne by various notable figures, including military leaders, athletes, and artists.
  • D. Vautrin
    Vautrin is a cunning, charismatic criminal mastermind and recurring antihero in Honoré de Balzac’s La Comédie humaine, known for his manipulative intelligence and complex moral ambiguity.
  • E. Confignon
    Confignon is a small municipality in the canton of Geneva in southwestern Switzerland, known for its residential character and proximity to the city of Geneva.
  • 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_69ad8586a34c8190944c63ec11a8de1a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada66facf881908b9ec687d68ce91b completed March 8, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69b24b66b3e081908e8ea11d9b36e50a completed March 12, 2026, 5:13 a.m.
NEDg Description generation batch_69b24f6f5ee08190b42e2ae0610c34d3 completed March 12, 2026, 5:30 a.m.
NED2 Entity disambiguation (via description) batch_69b24ff7eff88190973925ae3ef804c7 completed March 12, 2026, 5:32 a.m.
Created at: March 8, 2026, 3:06 p.m.