Triple

T16591163
Position Surface form Disambiguated ID Type / Status
Subject Zhichun Road station E403088 entity
Predicate hasLine P35 FINISHED
Object Line 10 E66117 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 10 | Statement: [Zhichun Road station, hasLine, Line 10]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 10
Context triple: [Zhichun Road station, hasLine, Line 10]
  • A. Line 10 chosen
    Line 10 is a major loop line of the Beijing Subway that encircles central urban districts and serves as a key transfer route in the network.
  • B. Line 10
    Line 10 is a major Shanghai Metro route known for serving central districts and key hubs such as Hongqiao Transportation Hub and the city’s historic and commercial areas.
  • C. Line 10
    Line 10 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving key residential and commercial districts.
  • D. Line 10
    Line 10 is a rapid transit line of the Nanjing Metro system in Nanjing, China, serving as part of the city's urban rail network.
  • E. Line 10
    Line 10 is a rapid transit line of the Chongqing Metro system in Chongqing, China, providing urban rail service across parts of the municipality.
  • 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_69d88387363c8190a97a0c942130de97 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e359a012e081909a0604dde3c04bbb completed April 18, 2026, 10:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00759b9e5081909815d2cd00d44490 completed May 10, 2026, 12:10 p.m.
Created at: April 10, 2026, 5:16 a.m.