Triple
T2952793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LinkPass |
E79858
|
entity |
| Predicate | fareCoverage |
P38809
|
FINISHED |
| Object | local bus and subway |
—
|
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: local bus and subway | Statement: [LinkPass, fareCoverage, local bus and subway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fareCoverage Context triple: [LinkPass, fareCoverage, local bus and subway]
-
A.
medicalCoverageAfter
Indicates that one entity’s medical insurance coverage begins or applies after the time, event, or coverage period associated with another entity.
-
B.
providesCoverage
Indicates that one entity supplies protection, insurance, or service coverage to another entity or for a specified risk or scope.
-
C.
guaranteeCoverage
Indicates that one party commits to providing financial or protective coverage for another party or specified situation.
-
D.
typeOfCoverage
chosen
Indicates the specific kind or category of coverage that applies in a given context (such as insurance, service, or protection).
-
E.
typicallyCovers
Indicates that one entity is the kind of thing that usually or normally includes, addresses, or encompasses another entity.
- 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_69ad8b1276588190a374a0b12e0f7bdf |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad98fe4b688190a0f68c4f80cd6f8f |
completed | March 8, 2026, 3:42 p.m. |
| PD | Predicate disambiguation | batch_69ad960a70ac8190816b5ae3e8631031 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:57 p.m.