Triple

T3489241
Position Surface form Disambiguated ID Type / Status
Subject Fuxingmen station E73684 entity
Predicate hasStationLayout P15899 FINISHED
Object Line 1 runs east–west E332214 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 1 runs east–west | Statement: [Fuxingmen station, hasStationLayout, Line 1 runs east–west]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 1 runs east–west
Context triple: [Fuxingmen station, hasStationLayout, Line 1 runs east–west]
  • A. Line 1
    Line 1 is the first operational corridor of the Mumbai Monorail system, serving as a key elevated transit route in Mumbai, India.
  • B. Line 1
    Line 1 is the oldest and one of the busiest lines of the Mexico City Metro, running east–west across the city and serving many central, high-traffic stations.
  • C. Line 1
    Line 1 is a major north–south rapid transit line of the Shanghai Metro and one of the system’s oldest and busiest routes.
  • D. Line 1
    Line 1 is the oldest and one of the busiest lines of the Paris Métro, running primarily east–west through central Paris and serving many major landmarks.
  • E. Line 1 chosen
    Line 1 is a major Beijing Subway route that runs north–south through the city’s central axis, serving key commercial and historical areas.
  • 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_69ad85cca8d4819088494e9f3340fab5 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbb92b3ac8190b8675f5a5e9d4408 completed March 8, 2026, 6:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69b373bb0e00819087899a394f50295d completed March 13, 2026, 2:17 a.m.
Created at: March 8, 2026, 3:18 p.m.