Triple

T2478245
Position Surface form Disambiguated ID Type / Status
Subject Montmartre E55139 entity
Predicate near P350 FINISHED
Object Pigalle
Pigalle is a lively Parisian neighborhood known for its nightlife, cabarets, and proximity to Montmartre and the Moulin Rouge.
 E269904 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: Pigalle | Statement: [Montmartre, near, Pigalle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Pigalle
Context triple: [Montmartre, near, Pigalle]
  • A. Renault–Gitane
    Renault–Gitane was a dominant French professional cycling team of the late 1970s and early 1980s, known for nurturing multiple Grand Tour champions and pioneering modern team tactics.
  • B. La Coupée
    La Coupée is a dramatic, narrow isthmus with steep cliffs and a coastal road that forms the striking land bridge between the main island of Sark and Little Sark in the Channel Islands.
  • C. Biqueli
    Biqueli is a small coastal settlement on Atauro Island in East Timor, known for its fishing community and proximity to coral reefs.
  • D. Lusser
    Lusser is a German surname most notably associated with engineer Robert Lusser, known for his contributions to aeronautics and reliability engineering.
  • E. Traton
    Traton is a commercial vehicle manufacturer and holding company that oversees brands like MAN and Scania within the Volkswagen Group.
  • 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: Pigalle
Triple: [Montmartre, near, Pigalle]
Generated description
Pigalle is a lively Parisian neighborhood known for its nightlife, cabarets, and proximity to Montmartre and the Moulin Rouge.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Pigalle
Target entity description: Pigalle is a lively Parisian neighborhood known for its nightlife, cabarets, and proximity to Montmartre and the Moulin Rouge.
  • A. Renault–Gitane
    Renault–Gitane was a dominant French professional cycling team of the late 1970s and early 1980s, known for nurturing multiple Grand Tour champions and pioneering modern team tactics.
  • B. La Coupée
    La Coupée is a dramatic, narrow isthmus with steep cliffs and a coastal road that forms the striking land bridge between the main island of Sark and Little Sark in the Channel Islands.
  • C. Biqueli
    Biqueli is a small coastal settlement on Atauro Island in East Timor, known for its fishing community and proximity to coral reefs.
  • D. Lusser
    Lusser is a German surname most notably associated with engineer Robert Lusser, known for his contributions to aeronautics and reliability engineering.
  • E. Traton
    Traton is a commercial vehicle manufacturer and holding company that oversees brands like MAN and Scania within the Volkswagen Group.
  • 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_69ab49e279e88190ab10d7248aea9d11 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd14ef7d081909159be158bc0ce45 completed March 7, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69af17aea398819092cb14b93abd0ff7 completed March 9, 2026, 6:55 p.m.
NEDg Description generation batch_69af18f9af388190bbb4242c89d4272e completed March 9, 2026, 7:01 p.m.
NED2 Entity disambiguation (via description) batch_69af198534c0819090c742f39501fac6 completed March 9, 2026, 7:03 p.m.
Created at: March 6, 2026, 9:45 p.m.