Triple

T3155579
Position Surface form Disambiguated ID Type / Status
Subject Paris Métro Line 2 E65977 entity
Predicate renamedAs P65 FINISHED
Object Ligne 2
Ligne 2 is a Paris Métro line forming a semicircular route through northern Paris, known for serving major districts such as Pigalle and Belleville.
E331921 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: Ligne 2 | Statement: [Paris Métro Line 2, renamedAs, Ligne 2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ligne 2
Context triple: [Paris Métro Line 2, renamedAs, Ligne 2]
  • A. Line 2
    Line 2 is a major east–west rapid transit route of the Shanghai Metro that connects key commercial, residential, and airport hubs across the city.
  • B. Line 2
    Line 2 is a trolleybus route within Geneva’s public transport system that serves as one of the city’s main electric bus lines.
  • C. Line 2
    Line 2 is a rapid transit line of the Barcelona Metro system that serves several central and northern neighborhoods of the city.
  • D. Line 2
    Line 2 is a major rapid transit route of the Guangzhou Metro system that runs through key urban districts and serves as one of the network’s primary north–south corridors.
  • E. Line 2
    Line 2 is a major subway line on Toronto's Bloor–Danforth corridor, running primarily east–west across the city.
  • 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: Ligne 2
Triple: [Paris Métro Line 2, renamedAs, Ligne 2]
Generated description
Ligne 2 is a Paris Métro line forming a semicircular route through northern Paris, known for serving major districts such as Pigalle and Belleville.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ligne 2
Target entity description: Ligne 2 is a Paris Métro line forming a semicircular route through northern Paris, known for serving major districts such as Pigalle and Belleville.
  • A. Line 2
    Line 2 is a major east–west rapid transit route of the Shanghai Metro that connects key commercial, residential, and airport hubs across the city.
  • B. Line 2
    Line 2 is a major rapid transit route of the Guangzhou Metro system that runs through key urban districts and serves as one of the network’s primary north–south corridors.
  • C. Line 2
    Line 2 is a trolleybus route within Geneva’s public transport system that serves as one of the city’s main electric bus lines.
  • D. Line 2
    Line 2 is a rapid transit line of the Barcelona Metro system that serves several central and northern neighborhoods of the city.
  • E. Line 2
    Line 2 is a circular rapid transit line of the Beijing Subway that runs around the city center, roughly following the path of the old city walls and the 2nd Ring Road.
  • 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_69ad8584485081909ed529e890cadc4a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada5e97548819084643586fff2e3cb completed March 8, 2026, 4:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b225068444819080e2b8b6b1260613 completed March 12, 2026, 2:29 a.m.
NEDg Description generation batch_69b22574e7c881908e9645f0869d95a8 completed March 12, 2026, 2:31 a.m.
NED2 Entity disambiguation (via description) batch_69b225f0e0b0819096f8b5f7e7ddd8c3 completed March 12, 2026, 2:33 a.m.
Created at: March 8, 2026, 3:05 p.m.