Triple
T5884308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hong Kong Government Cantonese Romanization |
E130822
|
entity |
| Predicate | usedOnMTRStationNames |
P67258
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Hong Kong Government Cantonese Romanization, usedOnMTRStationNames, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedOnMTRStationNames Context triple: [Hong Kong Government Cantonese Romanization, usedOnMTRStationNames, yes]
-
A.
stationName
Indicates the name assigned to a particular station in the relationship.
-
B.
connectsToRailStation
Indicates that one entity has a direct link, route, or access connection to a rail station.
-
C.
subwayStation
Indicates that one entity is a subway station associated with, located in, or serving the other entity.
-
D.
interchangeStation
Indicates a station where passengers can transfer between different routes, lines, or modes of transportation.
-
E.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
- 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_69c0085628dc8190b334c1b44c067efc |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03fe07b7081909f8577ec3a9a1a8d |
completed | March 22, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69c0334bdc308190ad0d7199ab975588 |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c03fdf954c8190ae97a5c9ce40bdfa |
completed | March 22, 2026, 7:15 p.m. |
Created at: March 22, 2026, 3:57 p.m.