Triple
T12714046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western Harbour Crossing |
E303791
|
entity |
| Predicate | harbourCrossingNumber |
P106310
|
FINISHED |
| Object | third road harbour crossing in Hong Kong |
—
|
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: third road harbour crossing in Hong Kong | Statement: [Western Harbour Crossing, harbourCrossingNumber, third road harbour crossing in Hong Kong]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: harbourCrossingNumber Context triple: [Western Harbour Crossing, harbourCrossingNumber, third road harbour crossing in Hong Kong]
-
A.
crossingOf
Indicates that one entity serves as the intersection or crossing point of two or more linear features, such as roads, paths, or tracks.
-
B.
hadCrossingPoints
Indicates that two entities intersected or overlapped at one or more specific points in space or time.
-
C.
hasBayCrossing
Indicates that one place is connected to another by a crossing over a bay, such as a bridge, tunnel, or ferry route.
-
D.
hasBridgeTypeCrossing
Indicates that a bridge is characterized by a specific type of crossing it provides or supports.
-
E.
hasNumberOfCrosses
Indicates the quantity of crosses associated with or present on a given entity.
- 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_69d7bdf084148190ab9d513dc0735af4 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9620a7554819083784897ff690652 |
completed | April 10, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69d960c088dc8190b0e63312c54e4c6c |
completed | April 10, 2026, 8:42 p.m. |
| PDg | Predicate description generation | batch_69d961acadb8819098de743bc951fedb |
completed | April 10, 2026, 8:46 p.m. |
Created at: April 9, 2026, 5:23 p.m.