Triple
T22337496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WJRT-TV |
E552188
|
entity |
| Predicate | locationCategory |
P16688
|
FINISHED |
| Object | Midwestern United States 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: Midwestern United States television station | Statement: [WJRT-TV, locationCategory, Midwestern United States television station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locationCategory Context triple: [WJRT-TV, locationCategory, Midwestern United States television station]
-
A.
placeType
chosen
Indicates the type or category of place associated with an entity (e.g., city, park, building).
-
B.
cityLocation
Indicates that a city is geographically situated within or associated with a specific larger area or place.
-
C.
locationScrapped
Indicates that the location associated with an entity has been removed, discarded, or is no longer considered valid or in use.
-
D.
regionClassification
Indicates how a given area or location is categorized into a specific region based on defined criteria or boundaries.
-
E.
typeLocality
Indicates the specific geographic location where a specimen or taxon was originally found and formally described.
- 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_69e11e494eec81909c4d2d51f69499d9 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157804e60819094e2a903ace6f4b2 |
completed | April 29, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e7300c20088190a59e5bf9e70384f3 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:43 p.m.