Triple
T759312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MetroAccess |
E16029
|
entity |
| Predicate | serviceMode |
P1533
|
FINISHED |
| Object | van |
—
|
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: van | Statement: [MetroAccess, serviceMode, van]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceMode Context triple: [MetroAccess, serviceMode, van]
-
A.
servesMode
chosen
Indicates that one entity provides or operates in a particular manner, method, or mode in relation to another entity or context.
-
B.
serviceWith
Indicates that one entity provides or is associated with a particular service offered to or used by another entity.
-
C.
service
Indicates that one entity performs work, assistance, or functions to meet the needs or requests of another entity.
-
D.
serviceDuring
Indicates that one entity performs or provides a service for another entity during a specified time period or event.
-
E.
serviceUniform
Indicates that one entity is wearing or associated with a standardized uniform used for official or professional service.
- 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_69a493684ee48190bd43b7c78da4aec8 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a67f9778819098d3c144dd26b976 |
completed | March 1, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69a4a50348088190873a1446db657a78 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.