Triple
T33978002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsing Yi station |
E871193
|
entity |
| Predicate | adjacentStationOnAirportExpress |
P186490
|
FINISHED |
| Object | Kowloon station |
—
|
NE NERFINISHED |
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 | Statement: [Tsing Yi station, adjacentStationOnAirportExpress, Kowloon station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentStationOnAirportExpress Context triple: [Tsing Yi station, adjacentStationOnAirportExpress, Kowloon station]
-
A.
adjacentToStation
Indicates that one entity is located next to or immediately beside a station.
-
B.
adjacentStationOnNaritaLine
Indicates that one station is directly next to another station along the Narita railway line, with no other stations in between.
-
C.
adjacentStationOnCapitalLine
Indicates that one station is directly next to another station along the Capital Line, with no other stations in between.
-
D.
adjacentStationOnTsukubaExpress
Indicates that one station is directly next to another station along the Tsukuba Express railway line, with no other stations in between.
-
E.
adjacentStationOnDisneylandResortLine
Indicates that one station is directly next to another station along the Disneyland Resort Line, with no other stations in between.
- F. None of above. chosen
Provenance (4 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_69f3499da0188190ab1a4ff06fb06a2a |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f9fe1a1ca4819084c196f0041f0be2 |
completed | May 5, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69f7cf769338819092a5f42653dcc956 |
completed | May 3, 2026, 10:43 p.m. |
| PDg | Predicate description generation | batch_69f9fd66eed48190bdc26a8def328c2d |
completed | May 5, 2026, 2:23 p.m. |
Created at: May 1, 2026, 1:50 a.m.