Triple
T137425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Washington Metropolitan Area Transit Authority |
E2776
|
entity |
| Predicate | providesServiceType |
P849
|
FINISHED |
| Object | public transportation |
—
|
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: public transportation | Statement: [Washington Metropolitan Area Transit Authority, providesServiceType, public transportation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: providesServiceType Context triple: [Washington Metropolitan Area Transit Authority, providesServiceType, public transportation]
-
A.
hasServiceType
chosen
Indicates that an entity is associated with or categorized by a particular type of service.
-
B.
servedByService
Indicates that something is provided, handled, or fulfilled by a particular service.
-
C.
typeOfSupport
Indicates the kind or category of assistance, help, or backing provided in a given context.
-
D.
sectorServed
Indicates the industry or economic sector that an entity primarily serves or targets with its activities, products, or services.
-
E.
service
Indicates that one entity performs work, assistance, or functions to meet the needs or requests of 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257a6cab88190944c8f74d8d1605c |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a25652efdc8190b85b33735a9e6370 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.