Triple

T12835851
Position Surface form Disambiguated ID Type / Status
Subject Fair Park station E306909 entity
Predicate servedByLine P1293 FINISHED
Object Green Line
The Green Line is a public transit rail route that serves stations such as Fair Park within its metropolitan network.
E189932 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: Green Line | Statement: [Fair Park station, servedByLine, Green Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Green Line
Context triple: [Fair Park station, servedByLine, Green Line]
  • A. Green Line
    The Green Line is one of Chicago's elevated rapid transit routes, running primarily along the city's West and South Sides as part of the Chicago "L" system.
  • B. Green Line
    The Green Line was the former name of Los Angeles Metro's C Line, a light rail route serving the South Bay region and connecting to LAX via nearby stations.
  • C. Green Line
    The Green Line is a light rail service route within the San Diego Trolley system that connects key destinations across the San Diego metropolitan area.
  • D. Green Line
    The Green Line is a light rail service operated as part of Cleveland's RTA Rapid Transit system.
  • E. Green Line
    The Green Line is one of the main light rail routes of Dublin’s Luas tram system, serving key suburbs and city areas along its corridor.
  • 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: Green Line
Triple: [Fair Park station, servedByLine, Green Line]
Generated description
The Green Line is a public transit rail route that serves stations such as Fair Park within its metropolitan network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Green Line
Target entity description: The Green Line is a public transit rail route that serves stations such as Fair Park within its metropolitan network.
  • A. Green Line
    The Green Line is one of the light rail routes in Houston’s METRORail system, serving the city’s East End and connecting it to downtown.
  • B. Green Line chosen
    The Green Line is a light rail route in Dallas, Texas, operated by Dallas Area Rapid Transit (DART), running through key areas including downtown and connecting several suburbs.
  • C. Green Line
    The Green Line is a public transit route, likely part of an urban rail or metro system, that intersects with the Purple Line Express.
  • D. Green Line
    The Green Line is a light rail service within Salt Lake City's TRAX system that connects key destinations across the metropolitan area.
  • E. Green Line
    The Green Line is a rapid transit route within Miami-Dade County's Metrorail system, providing north-south rail service through key urban neighborhoods and connections.
  • 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_69d7bdf52b94819096d6f0ba4ab50a98 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96ff015f4819090070a01f3938acc completed April 10, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6a54838888190804202e45a55de48 completed May 3, 2026, 1:30 a.m.
NEDg Description generation batch_69f6a616f6e4819096c9850434882548 completed May 3, 2026, 1:34 a.m.
NED2 Entity disambiguation (via description) batch_69f6a716bb2c81909dccc5ddbf3c92b5 completed May 3, 2026, 1:38 a.m.
Created at: April 9, 2026, 5:35 p.m.