Triple

T34806232
Position Surface form Disambiguated ID Type / Status
Subject Austin Station (MTR) E1003364 entity
Predicate isInterchangeWith P30943 FINISHED
Object Kowloon Station (MTR)
Kowloon Station (MTR) is a major underground railway station in Hong Kong serving the Tung Chung Line and the Airport Express, and is integrated with the Union Square commercial and residential complex above it.
E2171226 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: Kowloon Station (MTR) | Statement: [Austin Station (MTR), isInterchangeWith, Kowloon Station (MTR)]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kowloon Station (MTR)
Triple: [Austin Station (MTR), isInterchangeWith, Kowloon Station (MTR)]
Generated description
Kowloon Station (MTR) is a major underground railway station in Hong Kong serving the Tung Chung Line and the Airport Express, and is integrated with the Union Square commercial and residential complex above it.

Provenance (5 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_69f76db600b88190989abdf08fce3b27 completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f77a8e286481909852ed240c92b4aa completed May 3, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a390d27217c8190ba7de8cd5b44290f completed June 22, 2026, 10:23 a.m.
NEDg Description generation batch_6a390dd6ff808190bdd0b30b261092f5 completed June 22, 2026, 10:26 a.m.
NED2 Entity disambiguation (via description) batch_6a390f2d062481908c4789fba5096e69 completed June 22, 2026, 10:32 a.m.
Created at: May 3, 2026, 3:59 p.m.