Triple

T2445424
Position Surface form Disambiguated ID Type / Status
Subject Bernex E53379 entity
Predicate hasLocality P7943 FINISHED
Object Champs-Lambert
Champs-Lambert is a locality within the municipality of Bernex in the canton of Geneva, Switzerland.
E267123 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: Champs-Lambert | Statement: [Bernex, hasLocality, Champs-Lambert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Champs-Lambert
Context triple: [Bernex, hasLocality, Champs-Lambert]
  • A. Trottier
    Trottier is a surname most prominently associated with Bryan Trottier, a Hall of Fame Canadian-American ice hockey player and multiple Stanley Cup champion.
  • B. Virage Chatillon
    Virage Chatillon is a French youth football club known for being one of the early teams in Thierry Henry’s development.
  • C. Lebrun
    Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
  • D. Grand Veymont
    Grand Veymont is a prominent mountain peak in the French Prealps, known for its panoramic views and popular hiking routes within the Vercors region.
  • E. Lusser
    Lusser is a German surname most notably associated with engineer Robert Lusser, known for his contributions to aeronautics and reliability engineering.
  • 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: Champs-Lambert
Triple: [Bernex, hasLocality, Champs-Lambert]
Generated description
Champs-Lambert is a locality within the municipality of Bernex in the canton of Geneva, Switzerland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Champs-Lambert
Target entity description: Champs-Lambert is a locality within the municipality of Bernex in the canton of Geneva, Switzerland.
  • A. Trottier
    Trottier is a surname most prominently associated with Bryan Trottier, a Hall of Fame Canadian-American ice hockey player and multiple Stanley Cup champion.
  • B. Virage Chatillon
    Virage Chatillon is a French youth football club known for being one of the early teams in Thierry Henry’s development.
  • C. Lebrun
    Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
  • D. Grand Veymont
    Grand Veymont is a prominent mountain peak in the French Prealps, known for its panoramic views and popular hiking routes within the Vercors region.
  • E. Lusser
    Lusser is a German surname most notably associated with engineer Robert Lusser, known for his contributions to aeronautics and reliability engineering.
  • 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_69ab495b6dac8190ac82661aa1452222 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abca23ebe8819099a579a07c1bb708 completed March 7, 2026, 6:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef0baa6448190a4046a039168b8fe completed March 9, 2026, 4:09 p.m.
NEDg Description generation batch_69aef58eff2c81909cbf3346705940a3 completed March 9, 2026, 4:30 p.m.
NED2 Entity disambiguation (via description) batch_69aef656ae0c81908753cc5a8b5fe704 completed March 9, 2026, 4:33 p.m.
Created at: March 6, 2026, 9:43 p.m.