Triple

T15092143
Position Surface form Disambiguated ID Type / Status
Subject Dongsi Shitiao station E360445 entity
Predicate isOnLoopLine P48914 FINISHED
Object Line 2 E768291 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: Line 2 | Statement: [Dongsi Shitiao station, isOnLoopLine, Line 2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 2
Context triple: [Dongsi Shitiao station, isOnLoopLine, Line 2]
  • A. Line 2
    Line 2 is a trolleybus route within Geneva’s public transport system that serves as one of the city’s main electric bus lines.
  • B. Line 2
    Line 2 is a rapid transit line of the Barcelona Metro system that serves several central and northern neighborhoods of the city.
  • C. Line 2
    Line 2 is a major rapid transit route of the STC Metro system, serving key districts along one of the network’s primary corridors.
  • D. Line 2
    Line 2 is the Yellow Line of the Delhi Metro, a major rapid transit corridor connecting key areas across Delhi and its neighboring regions.
  • E. Line 2 chosen
    Line 2 is a major rapid transit line of the Chongqing Metro system in Chongqing, China, known for being one of the city's primary monorail corridors.
  • 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0027925788190b955fdc6626adf7d completed April 15, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69feb7e47b20819084145008474f47b7 completed May 9, 2026, 4:28 a.m.
Created at: April 10, 2026, 3:04 a.m.