Triple

T33183463
Position Surface form Disambiguated ID Type / Status
Subject Goutte d'Or E849398 entity
Predicate transportServedBy P1298 FINISHED
Object Barbès–Rochechouart metro station
Barbès–Rochechouart metro station is a major Paris Métro interchange in the 18th arrondissement, serving lines 2 and 4 near the Barbès and Rochechouart boulevards.
E2090826 NE FINISHED

How this triple was built (2 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: Barbès–Rochechouart metro station | Statement: [Goutte d'Or, transportServedBy, Barbès–Rochechouart metro station]
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: Barbès–Rochechouart metro station
Triple: [Goutte d'Or, transportServedBy, Barbès–Rochechouart metro station]
Generated description
Barbès–Rochechouart metro station is a major Paris Métro interchange in the 18th arrondissement, serving lines 2 and 4 near the Barbès and Rochechouart boulevards.

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_69f3495d06508190b0b7729982982cea completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d9a0608881909aa6db92c802c032 completed May 3, 2026, 5:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36f9a821d481908ffd5b01b0597793 completed June 20, 2026, 8:35 p.m.
NEDg Description generation batch_6a36fab9d4448190a49caae3e8f7c561 completed June 20, 2026, 8:40 p.m.
NED2 Entity disambiguation (via description) batch_6a36fb6882fc8190bd69194e3eabeb8f completed June 20, 2026, 8:43 p.m.
Created at: May 1, 2026, 1:29 a.m.