Triple

T35488985

Position	Surface form	Disambiguated ID	Type / Status
Subject	Sau Mau Ping	`E1025675`	entity
Predicate	nearbyMTRStation	`P188083`	FINISHED
Object	Kwun Tong station Kwun Tong station is a major Mass Transit Railway (MTR) station in Hong Kong’s Kowloon East area, serving as a key transport hub on the Kwun Tong line.	`E2259567`	NE FINISHED

How this triple was built (3 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: Kwun Tong station | Statement: [Sau Mau Ping, nearbyMTRStation, Kwun Tong 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: Kwun Tong station
Triple: [Sau Mau Ping, nearbyMTRStation, Kwun Tong station]

Generated description

Kwun Tong station is a major Mass Transit Railway (MTR) station in Hong Kong’s Kowloon East area, serving as a key transport hub on the Kwun Tong line.

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: nearbyMTRStation
Context triple: [Sau Mau Ping, nearbyMTRStation, Kwun Tong station]

A. nearbyLRTStation
Indicates that there is an LRT (light rail transit) station located close to the referenced place or entity.
B. nearbyMajorStation chosen
Indicates that one location is situated close to a major transportation station (such as a main train, bus, or metro hub).
C. nearestSuburbanRailwayStation
Indicates the relationship where a given place is associated with the suburban railway station that is geographically closest to it.
D. nearbyHeritageStation
Indicates that one entity is located close to a heritage (historically or culturally significant) station.
E. subwayServiceAtNearbyStation
Indicates that there is subway service available at a station located near the referenced place or entity.
F. None of above.

Provenance (6 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_69f76dfbcdd881908c7b0b6bc502252b`	completed	May 3, 2026, 3:47 p.m.
NER	Named-entity recognition	`batch_69feba0f09508190b3e871c62b19ec7f`	completed	May 9, 2026, 4:37 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a417b0e22708190abb207e101ab8beb`	completed	June 28, 2026, 7:50 p.m.
NEDg	Description generation	`batch_6a417dd5c4b48190a6630675b3952122`	completed	June 28, 2026, 8:02 p.m.
NED2	Entity disambiguation (via description)	`batch_6a417e4fbe288190a20979ce6399817a`	completed	June 28, 2026, 8:04 p.m.
PD	Predicate disambiguation	`batch_69feb957fe7c8190969fb31a6d1a59c8`	completed	May 9, 2026, 4:34 a.m.

Created at: May 3, 2026, 4:04 p.m.