Triple

T19397064
Position Surface form Disambiguated ID Type / Status
Subject Baishiqiao South station E485218 entity
Predicate hasLine P35 FINISHED
Object Line 6 — NE NERFINISHED

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 6 | Statement: [Baishiqiao South station, hasLine, Line 6]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 6
Context triple: [Baishiqiao South station, hasLine, Line 6]
  • A. Line 6
    Line 6 is a route of the Mexico City Metro system that runs east–west across the northern part of the city, connecting several residential and commercial areas.
  • B. Line 6
    Line 6 is a rapid transit line of the Shanghai Metro system serving several districts along the city’s eastern side.
  • C. Line 6
    Line 6 is a rapid transit line of the Chongqing Rail Transit system in Chongqing, China, serving key urban districts with high-capacity metro service.
  • D. Line 6
    Line 6 is a route of Mexico City’s Metrobús bus rapid transit system that serves as one of the network’s main corridors.
  • E. Line 6 chosen
    Line 6 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving multiple urban districts with frequent subway service.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d5162481909db12435d9535c1a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e62573f5788190a635b92121db2cf7 completed April 20, 2026, 1:09 p.m.
Created at: April 10, 2026, 1:36 p.m.