Triple
T11321979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trans-Harbour Line |
E268114
|
entity |
| Predicate | commuterUsage |
P19600
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Trans-Harbour Line, commuterUsage, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commuterUsage Context triple: [Trans-Harbour Line, commuterUsage, high]
-
A.
hasCommuterTraffic
chosen
Indicates that there is regular, recurring traffic flow associated with people traveling between their homes and places of work or study.
-
B.
commuterHubFor
Indicates a location that serves as a primary transit or gathering point for commuters traveling to or from another place.
-
C.
hasPublicTransportUsage
Indicates that an entity makes use of, or is associated with the use of, public transportation services.
-
D.
commuterDestination
Indicates that a location serves as the endpoint or target place to which a person regularly travels for commuting.
-
E.
passesUsedForTransportation
Indicates that the passes are utilized as a means or instrument for transporting people or goods.
- F. None of above.
Provenance (3 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9dff37081909622623e66e17ccd |
completed | April 9, 2026, 6:03 p.m. |
| PD | Predicate disambiguation | batch_69d787ad575081908274280bf75d95fd |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.