Triple

T34722682
Position Surface form Disambiguated ID Type / Status
Subject Hung Hom Estate E1000960 entity
Predicate hasNearbyPlace P3449 FINISHED
Object Whampoa MTR station
Whampoa MTR station is a Mass Transit Railway station in Hong Kong’s Kowloon area serving the Whampoa and Hung Hom neighborhoods as part of the Kwun Tong Line extension.
E2155320 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: Whampoa MTR station | Statement: [Hung Hom Estate, hasNearbyPlace, Whampoa MTR 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: Whampoa MTR station
Triple: [Hung Hom Estate, hasNearbyPlace, Whampoa MTR station]
Generated description
Whampoa MTR station is a Mass Transit Railway station in Hong Kong’s Kowloon area serving the Whampoa and Hung Hom neighborhoods as part of the Kwun Tong Line extension.

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_69f76daeb6e48190a4c9a6b0edc80f72 completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f779a436c88190a1f3aceab640202d completed May 3, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3885d2ecdc81909ae0f3af6d600799 completed June 22, 2026, 12:46 a.m.
NEDg Description generation batch_6a38875849188190a5f9af61de4904e0 completed June 22, 2026, 12:52 a.m.
NED2 Entity disambiguation (via description) batch_6a3888bbc4f481908007c1d0c99c9576 completed June 22, 2026, 12:58 a.m.
Created at: May 3, 2026, 3:59 p.m.