Triple
T12078838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matt Lauer |
E287623
|
entity |
| Predicate | hasWorkedFor |
P11675
|
FINISHED |
| Object |
WNEW-TV
WNEW-TV is a New York City television station historically known as an independent outlet that later became part of the Fox network.
|
E963612
|
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: WNEW-TV | Statement: [Matt Lauer, hasWorkedFor, WNEW-TV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WNEW-TV Context triple: [Matt Lauer, hasWorkedFor, WNEW-TV]
-
A.
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.
-
B.
WNYE-TV
WNYE-TV is a non-commercial educational television station serving the New York City area, operated by NYC Media and known for its locally focused and multicultural programming.
-
C.
WSAW-TV
WSAW-TV is a local television station serving the Wausau, Wisconsin area, providing news, weather, and entertainment programming to regional viewers.
-
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.
WGR-TV
WGR-TV is a Buffalo, New York television station that served as an early career platform for broadcaster and journalist Nick Clooney.
- 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: WNEW-TV Triple: [Matt Lauer, hasWorkedFor, WNEW-TV]
Generated description
WNEW-TV is a New York City television station historically known as an independent outlet that later became part of the Fox network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: WNEW-TV Target entity description: WNEW-TV is a New York City television station historically known as an independent outlet that later became part of the Fox network.
-
A.
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.
-
B.
WNYE-TV
WNYE-TV is a non-commercial educational television station serving the New York City area, operated by NYC Media and known for its locally focused and multicultural programming.
-
C.
WSAW-TV
WSAW-TV is a local television station serving the Wausau, Wisconsin area, providing news, weather, and entertainment programming to regional viewers.
-
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.
WGR-TV
WGR-TV is a Buffalo, New York television station that served as an early career platform for broadcaster and journalist Nick Clooney.
- 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9045e81f88190be2b1aabd93f077c |
completed | April 10, 2026, 2:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f66301f081909697f9dd444a099e |
completed | May 2, 2026, 1:04 p.m. |
| NEDg | Description generation | batch_69f5fde880f4819094b2170bf4e82138 |
completed | May 2, 2026, 1:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f5ffc563a08190b95db768df475a3a |
completed | May 2, 2026, 1:44 p.m. |
Created at: April 8, 2026, 9:48 p.m.