Triple
T254317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metrobus (Washington, D.C.) |
E5403
|
entity |
| Predicate | hasServiceFrequencyType |
P7407
|
FINISHED |
| Object | fixed-route scheduled 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: fixed-route scheduled service | Statement: [Metrobus (Washington, D.C.), hasServiceFrequencyType, fixed-route scheduled service]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasServiceFrequencyType Context triple: [Metrobus (Washington, D.C.), hasServiceFrequencyType, fixed-route scheduled service]
-
A.
hasServiceType
Indicates that an entity is associated with or categorized by a particular type of service.
-
B.
hasServiceTo
Indicates that one entity provides, offers, or operates a service for or directed toward another entity.
-
C.
tienePeriodicidad
chosen
Indicates that something occurs, recurs, or is scheduled with a specific regular frequency or periodic pattern.
-
D.
awardedFrequency
Indicates how often an award or recognition is given within a specified time period.
-
E.
servedByService
Indicates that something is provided, handled, or fulfilled by a particular 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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25d548cac819081b1636b2a057c62 |
completed | Feb. 28, 2026, 3:13 a.m. |
| PD | Predicate disambiguation | batch_69a25b694c08819085bb4b256fa7736f |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.