Triple
T12208034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The MacNeil/Lehrer Report |
E290884
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | WETA-TV |
E290881
|
NE 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: WETA-TV | Statement: [The MacNeil/Lehrer Report, productionCompany, WETA-TV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WETA-TV Context triple: [The MacNeil/Lehrer Report, productionCompany, WETA-TV]
-
A.
WETA-TV
chosen
WETA-TV is a Washington, D.C.–based public television station and major PBS member known for producing flagship national programs such as PBS NewsHour.
-
B.
WETA
WETA is the Water Emergency Transportation Authority, the public agency that oversees and operates ferry services in the San Francisco Bay Area.
-
C.
KDKA-TV
KDKA-TV is a Pittsburgh-based television station and major CBS affiliate known as one of the pioneering commercial TV outlets in the United States.
-
D.
WTAE-TV
WTAE-TV is a Pittsburgh-based television station that serves as the local ABC network affiliate.
-
E.
KYW-TV
KYW-TV is a CBS-owned-and-operated television station serving the Philadelphia, Pennsylvania market.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91c7d8f5c8190a46e9caa2a920fa9 |
completed | April 10, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63ee694848190a1362934110b6ceb |
completed | May 2, 2026, 6:13 p.m. |
Created at: April 8, 2026, 9:51 p.m.