Triple
T617344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metro Bus |
E14434
|
entity |
| Predicate | operatingSchedule |
P10069
|
FINISHED |
| Object | daily service |
—
|
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: daily service | Statement: [Metro Bus, operatingSchedule, daily service]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatingSchedule Context triple: [Metro Bus, operatingSchedule, daily service]
-
A.
hoursOfOperation
Indicates the time periods during which a place or service is open and available for use.
-
B.
operatesAllTimes
Indicates that the action, service, or process is continuously in operation at all times without interruption.
-
C.
daysOfOperation
chosen
Indicates the specific days on which an entity (such as a service, facility, or operation) is active or functioning.
-
D.
typicalSchedule
Indicates the usual or standard timing and sequence of activities or events associated with an entity.
-
E.
operatedDuring
Indicates that an action, process, or system was functioning or in operation throughout a specified time period or event.
- 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_69a4934b17c881909ace8270e8ddd202 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e2418c881908552d2c4a5006e97 |
completed | March 1, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69a49cfd15288190b4abdbd0bce3edcd |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.