Triple
T10496850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wausau, Wisconsin |
E247558
|
entity |
| Predicate | hasMedia |
P7961
|
FINISHED |
| Object |
WAOW-TV
WAOW-TV is a local television station serving the Wausau, Wisconsin area, providing news, weather, sports, and entertainment programming.
|
E867163
|
NE FINISHED |
How this triple was built (4 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: WAOW-TV | Statement: [Wausau, Wisconsin, hasMedia, WAOW-TV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WAOW-TV Context triple: [Wausau, Wisconsin, hasMedia, WAOW-TV]
-
A.
WABI-TV
WABI-TV is a long-running CBS-affiliated television station serving the Bangor, Maine market with local news, weather, and entertainment programming.
-
B.
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.
-
C.
WTAE-TV
WTAE-TV is a Pittsburgh-based television station that serves as the local ABC network affiliate.
-
D.
WIVB-TV
WIVB-TV is a television station serving the Buffalo, New York market, known for its local news and CBS-affiliated programming.
-
E.
WKRC-TV
WKRC-TV is a Cincinnati-based television station known for its local news coverage and for having notable broadcasters such as Nick Clooney among its on-air talent.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: WAOW-TV Triple: [Wausau, Wisconsin, hasMedia, WAOW-TV]
Generated description
WAOW-TV is a local television station serving the Wausau, Wisconsin area, providing news, weather, sports, and entertainment programming.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: WAOW-TV Target entity description: WAOW-TV is a local television station serving the Wausau, Wisconsin area, providing news, weather, sports, and entertainment programming.
-
A.
WABI-TV
WABI-TV is a long-running CBS-affiliated television station serving the Bangor, Maine market with local news, weather, and entertainment programming.
-
B.
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.
-
C.
WTAE-TV
WTAE-TV is a Pittsburgh-based television station that serves as the local ABC network affiliate.
-
D.
WIVB-TV
WIVB-TV is a television station serving the Buffalo, New York market, known for its local news and CBS-affiliated programming.
-
E.
WKRC-TV
WKRC-TV is a Cincinnati-based television station known for its local news coverage and for having notable broadcasters such as Nick Clooney among its on-air talent.
- F. None of above. chosen
Provenance (5 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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5098cd82c8190b44127a66c9c75ae |
completed | April 7, 2026, 1:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8dcbafe9481908fb23cfdf150adac |
completed | April 10, 2026, 11:19 a.m. |
| NEDg | Description generation | batch_69d8e8c8e360819085376d4c4ea9712d |
completed | April 10, 2026, 12:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d901fecee88190999e88ca2e56a516 |
completed | April 10, 2026, 1:58 p.m. |
Created at: April 6, 2026, 12:24 p.m.