Triple
T35170416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yau Ma Tei station |
E1015529
|
entity |
| Predicate | isBusyUrbanStation |
P91815
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [Yau Ma Tei station, isBusyUrbanStation, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isBusyUrbanStation Context triple: [Yau Ma Tei station, isBusyUrbanStation, true]
-
A.
isUrbanStation
Indicates that a station is located in an urban area or serves an urban environment.
-
B.
isBusiestStationIn
Indicates that a station has the highest level of activity (e.g., passenger or traffic volume) within a specified area or system.
-
C.
isSuburbanStationFor
Indicates that a station primarily serves a suburban area or functions as a transit hub for suburban commuters relative to a larger urban center.
-
D.
isBusyHub
chosen
Indicates that a location or node functions as a central point of activity with a high volume of interactions, traffic, or connections.
-
E.
isUrbanService
Indicates that a service operates within or is specifically intended for an urban area or city environment.
- F. None of above.
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_69f76ddbfde081908bffc91572368289 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78d3b0f0c81908e45789816ab70b4 |
completed | May 3, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69f78b9106008190930b3b3675b737d6 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4:02 p.m.