Triple
T527296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WNYW |
E10947
|
entity |
| Predicate | facilityType |
P2836
|
FINISHED |
| Object | full-power television station |
—
|
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: full-power television station | Statement: [WNYW, facilityType, full-power television station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: facilityType Context triple: [WNYW, facilityType, full-power television station]
-
A.
hasFacilityType
chosen
Indicates that an entity possesses or is associated with a specific type or category of facility.
-
B.
buildingType
Indicates the specific category or function that characterizes what kind of building something is.
-
C.
healthcareType
Indicates the category or kind of healthcare service, system, or coverage associated with an entity.
-
D.
homeFacilityCity
Indicates the city in which an entity’s primary or home facility is located.
-
E.
hasFacilities
Indicates that an entity possesses, provides, or is equipped with certain facilities or physical resources.
- 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1d2851c81908129f7da932ab7b3 |
completed | Feb. 28, 2026, 1:46 p.m. |
| PD | Predicate disambiguation | batch_69a2f0198ecc8190883849e5a8245963 |
completed | Feb. 28, 2026, 1:39 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.