Triple

T15928497
Position Surface form Disambiguated ID Type / Status
Subject Lyon tram line T2 E386264 entity
Predicate hasRouteNumber P1864 FINISHED
Object T2
T2 is a tram route in Lyon’s public transportation network, serving key districts between the city center and its southeastern suburbs.
E1184908 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: T2 | Statement: [Lyon tram line T2, hasRouteNumber, T2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: T2
Context triple: [Lyon tram line T2, hasRouteNumber, T2]
  • A. T2
    T2 is San Francisco International Airport’s Terminal 2, a modern passenger terminal serving domestic flights with updated amenities and design.
  • B. T2
    T2 is a passenger terminal at Berlin Brandenburg Airport that handles check-in, security, and boarding operations for departing and arriving travelers.
  • C. T2
    T2 is one of the tram lines of the Trambaix light rail network serving the Barcelona metropolitan area.
  • D. T2
    T2 is the second passenger terminal at Chicago O'Hare International Airport, serving various domestic and regional airline operations.
  • E. T2
    T2 is a shorthand title for the 1991 science fiction action film "Terminator 2: Judgment Day," directed by James Cameron and starring Arnold Schwarzenegger.
  • 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: T2
Triple: [Lyon tram line T2, hasRouteNumber, T2]
Generated description
T2 is a tram route in Lyon’s public transportation network, serving key districts between the city center and its southeastern suburbs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: T2
Target entity description: T2 is a tram route in Lyon’s public transportation network, serving key districts between the city center and its southeastern suburbs.
  • A. T2 chosen
    T2 is a tram line in the Lyon public transport network that connects key districts and suburbs of the city.
  • B. T2
    T2 is one of the main lines of the Dijon tramway system in Dijon, France, providing urban light-rail transit service across the city.
  • C. T2
    T2 is one of the tram lines of the Trambaix light rail network serving the Barcelona metropolitan area.
  • D. T2
    T2 is a Sydney Trains suburban rail service designation used for the Inner West & Leppington Line in the Sydney metropolitan network.
  • E. T2
    T2 is the second passenger terminal at Chicago O'Hare International Airport, serving various domestic and regional airline operations.
  • F. None of above.

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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156a39abc8190927818f6e185033a completed April 16, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffbe727c348190907c9e7a5db6031d completed May 9, 2026, 11:08 p.m.
NEDg Description generation batch_69ffbf3e80b08190899262a9d03c0e93 completed May 9, 2026, 11:11 p.m.
NED2 Entity disambiguation (via description) batch_69ffbfc0d1548190b7d2e9e10e837f0b completed May 9, 2026, 11:14 p.m.
Created at: April 10, 2026, 4:52 a.m.