Triple

T38103045
Position Surface form Disambiguated ID Type / Status
Subject MTR Tuen Ma line E951435 entity
Predicate hasStation P35 FINISHED
Object Sung Wong Toi station
Sung Wong Toi station is an underground MTR station in Hong Kong’s Kowloon City District serving the Tuen Ma line and named after the nearby historic Sung Wong Toi site.
E2286114 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: Sung Wong Toi station | Statement: [MTR Tuen Ma line, hasStation, Sung Wong Toi station]
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: Sung Wong Toi station
Triple: [MTR Tuen Ma line, hasStation, Sung Wong Toi station]
Generated description
Sung Wong Toi station is an underground MTR station in Hong Kong’s Kowloon City District serving the Tuen Ma line and named after the nearby historic Sung Wong Toi site.

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_69f76f065ed08190bdfb1b6d817f5b39 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fc45a428a48190b4cffbe8869aa56e completed May 7, 2026, 7:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a464b0ba2248190b88a253f6da98b27 completed July 2, 2026, 11:27 a.m.
NEDg Description generation batch_6a464bc92d8c81908e6a0ad938840123 completed July 2, 2026, 11:30 a.m.
NED2 Entity disambiguation (via description) batch_6a464c3d5e748190beae969583298369 completed July 2, 2026, 11:32 a.m.
Created at: May 3, 2026, 4:21 p.m.