Triple

T8401970
Position Surface form Disambiguated ID Type / Status
Subject Red Line (DART) E198393 entity
Predicate servesStation P839 FINISHED
Object Akard station E30234 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: Akard station | Statement: [Red Line (DART), servesStation, Akard station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Akard station
Context triple: [Red Line (DART), servesStation, Akard station]
  • A. Akard station chosen
    Akard station is a Dallas Area Rapid Transit (DART) light rail station serving the central business district of downtown Dallas, Texas.
  • B. Kedzie station
    Kedzie station is a Chicago 'L' rapid transit stop on the Brown Line serving the city's Northwest Side.
  • C. Luz Station
    Luz Station is a historic railway station and major transportation hub in São Paulo, Brazil, known for its distinctive architecture and cultural significance.
  • D. Rockwell station
    Rockwell station is an elevated Chicago 'L' rapid transit stop in the Lincoln Square neighborhood, serving passengers on the Brown Line.
  • E. Blaustein station
    Blaustein station is a local railway stop serving the town of Blaustein in the state of Baden-Württemberg, Germany.
  • 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_69ca8310df9c8190b25f16161cca3e41 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb824efa5c81908ce816cdb8e1fcfb completed March 31, 2026, 8:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69cde8789a608190a3503f544a19d204 completed April 2, 2026, 3:54 a.m.
Created at: March 30, 2026, 6:04 p.m.