Triple

T7663519
Position Surface form Disambiguated ID Type / Status
Subject Tech–35th E173566 entity
Predicate line P1293 FINISHED
Object Green Line E473597 NE FINISHED

How this triple was built (2 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: [Tech–35th, line, Green Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Green Line
Context triple: [Tech–35th, line, Green Line]
  • A. Green Line
    The Green Line is one of the main rapid transit routes of the Dubai Metro, serving key districts along Dubai Creek and connecting important commercial and residential areas.
  • B. Green Line
    Green Line is a hybrid-oriented trim level of the Saturn Aura midsize sedan designed to offer improved fuel efficiency and lower emissions.
  • C. Green Line
    The Green Line is one of the main rapid transit corridors of the Chennai Metro system in Chennai, India, connecting key areas of the city via elevated and underground stations.
  • D. 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.
  • E. Green Line chosen
    The Green Line is a light rail service within Salt Lake City's TRAX system that connects key destinations across the metropolitan area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c69955517c819085bc715b96d304d2 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c701a868bc8190b975cae769e23546 completed March 27, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c89b1aaef081908d1d181ea7c28c2f completed March 29, 2026, 3:23 a.m.
Created at: March 27, 2026, 3:59 p.m.