Triple

T17244427
Position Surface form Disambiguated ID Type / Status
Subject MARTA rail stations E418584 entity
Predicate hasLine P35 FINISHED
Object Blue Line
The Blue Line is one of MARTA’s primary heavy-rail transit routes serving key east–west corridors in the Atlanta metropolitan area.
E118566 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: [MARTA rail stations, hasLine, Blue Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blue Line
Context triple: [MARTA rail stations, hasLine, Blue Line]
  • A. 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.
  • B. 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.
  • C. Blue Line
    The Blue Line is one of the color-coded rapid transit routes in the Washington Metro system, running through key parts of Washington, D.C. and its Virginia suburbs.
  • D. 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.
  • E. Blue Line
    The Blue Line is a primary light rail route of the San Diego Trolley system, running through key corridors of the San Diego metropolitan area.
  • 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: [MARTA rail stations, hasLine, Blue Line]
Generated description
The Blue Line is one of MARTA’s primary heavy-rail transit routes serving key east–west corridors in the Atlanta metropolitan area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Blue Line
Target entity description: The Blue Line is one of MARTA’s primary heavy-rail transit routes serving key east–west corridors in the Atlanta metropolitan area.
  • A. Blue Line chosen
    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.
  • B. Blue Line
    The Blue Line is a primary route of the Baltimore Light Rail system that provides north–south rail transit service through the Baltimore metropolitan area.
  • C. Blue Line
    The Blue Line is a primary route of Charlotte's LYNX light rail system, providing major north–south transit service through the city.
  • D. Blue Line
    The Blue Line is one of the color-coded rapid transit routes in the Washington Metro system, running through key parts of Washington, D.C. and its Virginia suburbs.
  • E. Blue Line
    The Blue Line is one of the Montreal Metro’s rapid transit lines, running east–west to serve several central and northeastern neighborhoods of the city.
  • 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_69d886d8e96081909870bff6c3d0bf09 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42e22fb2c8190aea5d3872095bf46 completed April 19, 2026, 1:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0170e5d38881908d6f57a8bd60c930 completed May 11, 2026, 6:02 a.m.
NEDg Description generation batch_6a0172195dd8819096a9ff8a52170d38 completed May 11, 2026, 6:07 a.m.
NED2 Entity disambiguation (via description) batch_6a01725cb80c8190a43f6b2e39d1cb9c completed May 11, 2026, 6:08 a.m.
Created at: April 10, 2026, 5:39 a.m.