Triple
T9747114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RKO General |
E236338
|
entity |
| Predicate | owned |
P347
|
FINISHED |
| Object | WOR-TV |
E65996
|
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: WOR-TV | Statement: [RKO General, owned, WOR-TV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WOR-TV Context triple: [RKO General, owned, WOR-TV]
-
A.
WWOR-TV
chosen
WWOR-TV is a New York–area television station, historically known as a major independent and later network-affiliated outlet serving the New York City metropolitan market.
-
B.
WTN
WTN is the IATA airport code for RAF Waddington, a Royal Air Force station in Lincolnshire, England.
-
C.
WGR-TV
WGR-TV is a Buffalo, New York television station that served as an early career platform for broadcaster and journalist Nick Clooney.
-
D.
WABI-TV
WABI-TV is a long-running CBS-affiliated television station serving the Bangor, Maine market with local news, weather, and entertainment programming.
-
E.
WSTM-TV
WSTM-TV is a television station serving the Syracuse, New York market, known for its local news programming and affiliation with major broadcast networks.
- 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_69ca84d3e24481908a476e2231123cf9 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9f677830819096d388b9c798ecd5 |
completed | April 1, 2026, 10:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1b00d76488190af68cba694dc329c |
completed | April 5, 2026, 12:42 a.m. |
Created at: March 30, 2026, 8:23 p.m.