Triple

T15980549
Position Surface form Disambiguated ID Type / Status
Subject Snowdon station E387559 entity
Predicate connectsLine P845 FINISHED
Object Blue Line
The Blue Line is a public transit route that serves Snowdon station as part of its network.
E1188438 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: Blue Line | Statement: [Snowdon station, connectsLine, Blue Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blue Line
Context triple: [Snowdon station, connectsLine, Blue Line]
  • A. Blue Line
    The Blue Line is one of the main lines of the Lisbon Metro system, serving key central and northern areas of Portugal’s capital city.
  • B. Blue Line
    The Blue Line is a light rail route in the Dallas Area Rapid Transit (DART) system serving key neighborhoods and suburbs in the Dallas–Fort Worth metroplex.
  • C. Blue Line
    The Blue Line is one of the primary routes of the MetroLink light rail system serving the St. Louis metropolitan area.
  • D. Blue Line
    The Blue Line is a planned rapid transit corridor of Bengaluru’s Namma Metro network intended to expand connectivity across additional parts of the city.
  • E. Blue Line
    The Blue Line is one of the aerial cable car routes in La Paz–El Alto’s Mi Teleférico urban transit system, providing high-altitude public transportation across the Bolivian cities.
  • 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: Blue Line
Triple: [Snowdon station, connectsLine, Blue Line]
Generated description
The Blue Line is a public transit route that serves Snowdon station as part of its network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Blue Line
Target entity description: The Blue Line is a public transit route that serves Snowdon station as part of its network.
  • A. Blue Line
    Blue Line is a light rail service route within Salt Lake City’s TRAX public transit system, connecting key areas of the metropolitan region.
  • B. Blue Line
    The Blue Line is one of the primary light rail transit routes in Calgary's CTrain system, serving key corridors across the city.
  • C. Blue Line
    The Blue Line is a light rail service in Pittsburgh's public transit system that connects downtown with several southern suburbs.
  • D. Blue Line
    The Blue Line is one of the primary heavy-rail transit routes in Atlanta’s MARTA system, running east–west across the metropolitan area and serving key urban and suburban stations.
  • E. Blue Line
    The Blue Line is one of the major corridors of the Delhi Metro rapid transit system, connecting key residential and commercial areas across Delhi and its neighboring regions.
  • 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_69d86da94ccc819083d187f5dc6a123e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e157542cd88190832e7ae79bd38ffc completed April 16, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffc3b717c88190b974a44470136ff2 completed May 9, 2026, 11:31 p.m.
NEDg Description generation batch_69ffc5444c1c8190854de5575b9ec1c5 completed May 9, 2026, 11:37 p.m.
NED2 Entity disambiguation (via description) batch_69ffc5b95290819098b28c44c22b2799 completed May 9, 2026, 11:39 p.m.
Created at: April 10, 2026, 4:54 a.m.