Triple
T38333623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Route 2 (Hong Kong) |
E1037890
|
entity |
| Predicate | harbourCrossing |
P190793
|
FINISHED |
| Object | Eastern Harbour Crossing |
—
|
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: Eastern Harbour Crossing | Statement: [Route 2 (Hong Kong), harbourCrossing, Eastern Harbour Crossing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: harbourCrossing Context triple: [Route 2 (Hong Kong), harbourCrossing, Eastern Harbour Crossing]
-
A.
harbourSide
Indicates a location or object that is situated alongside or directly adjacent to a harbour.
-
B.
harbourCity
Indicates that a city serves as a harbour or port, providing maritime access and facilities for ships.
-
C.
harbourCrossingNumber
Indicates the specific numbered instance or count of a harbour crossing associated with an entity or event.
-
D.
harbourName
Indicates the name assigned to a harbour in which an entity is located or associated.
-
E.
harbourAlsoKnownAs
Indicates that a harbour is referred to by an alternative name or alias.
- 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_69f76e20d65c81909619ac0dd85c56f0 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fcd1499e2c81909bafd84dc4810f45 |
completed | May 7, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69fcccf024ec819086383ffbb6cfc036 |
completed | May 7, 2026, 5:33 p.m. |
| PDg | Predicate description generation | batch_69fcd148e6d4819082c118832ecc599b |
completed | May 7, 2026, 5:52 p.m. |
Created at: May 3, 2026, 4:30 p.m.