Triple
T12826536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MTR Tseung Kwan O Line |
E306665
|
entity |
| Predicate | hasCrossHarbourSection |
P107082
|
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: [MTR Tseung Kwan O Line, hasCrossHarbourSection, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrossHarbourSection Context triple: [MTR Tseung Kwan O Line, hasCrossHarbourSection, Yes]
-
A.
hasBayCrossing
Indicates that one place is connected to another by a crossing over a bay, such as a bridge, tunnel, or ferry route.
-
B.
hasBridgeSection
Indicates that one entity includes or is associated with a specific bridge section as a distinct part or component.
-
C.
hasCanalCrossing
Indicates that one entity is connected to or traversed by another via a canal crossing, such as a bridge, aqueduct, or similar structure over a canal.
-
D.
hasBridgeTypeCrossing
Indicates that a bridge is characterized by a specific type of crossing it provides or supports.
-
E.
hasBridgeCrossings
Indicates that one entity has one or more bridge structures that span across or connect over another entity (such as a road, river, or area).
- 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714208f881908f7f8a921362909a |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa08cd481909a946046ba63809f |
completed | April 10, 2026, 9:46 p.m. |
| PDg | Predicate description generation | batch_69d9713e45a88190acd346f066093550 |
completed | April 10, 2026, 9:53 p.m. |
Created at: April 9, 2026, 5:33 p.m.