Triple

T14357789
Position Surface form Disambiguated ID Type / Status
Subject An Jung-geun E356014 entity
Predicate placeOfEvent P373 FINISHED
Object Harbin railway station E694437 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: Harbin railway station | Statement: [An Jung-geun, placeOfEvent, Harbin railway station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harbin railway station
Context triple: [An Jung-geun, placeOfEvent, Harbin railway station]
  • A. Harbin Railway Station chosen
    Harbin Railway Station is a major railway hub in northeastern China, serving as a key gateway for passenger and freight transport in and around the city of Harbin.
  • B. Harbin West Railway Station
    Harbin West Railway Station is a major high-speed rail hub in Harbin, China, serving as a key gateway to the country's northeastern region.
  • C. Shenyang Railway Station
    Shenyang Railway Station is a major railway hub in Shenyang, China, serving as a key junction for regional and national rail services.
  • D. Shenyang North Railway Station
    Shenyang North Railway Station is a major passenger and transportation hub in Shenyang, China, serving as one of the city’s primary railway terminals.
  • E. Beihai railway station
    Beihai railway station is the main passenger rail hub serving the coastal city of Beihai in Guangxi, China, connecting it to regional and national rail networks.
  • 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_69d82790a7e08190877e2d349b2e8d8e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8f52ca7881908704eef20228aed3 completed April 14, 2026, 7:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bbd7cb881908b33b3aae4243f2e completed May 8, 2026, 3:42 a.m.
Created at: April 10, 2026, 1:15 a.m.