Triple
T9227987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melissa Stark |
E221736
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | WNBC-TV |
E11771
|
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: WNBC-TV | Statement: [Melissa Stark, employer, WNBC-TV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WNBC-TV Context triple: [Melissa Stark, employer, WNBC-TV]
-
A.
WNBC
chosen
WNBC is the primary NBC-owned television station serving the New York City metropolitan area.
-
B.
WNBC (Washington, D.C.)
WNBC (Washington, D.C.) was a major radio station that served as a prominent platform for influential broadcasters, including shock jock Howard Stern, during its operation.
-
C.
WABC-TV
WABC-TV is a New York City-based ABC-owned television station that produces and broadcasts local and nationally syndicated programming.
-
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.
WJZ-TV
WJZ-TV is a Baltimore-based television station that serves as a major local news and CBS network affiliate.
- 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_69ca83ec8db08190a9110df8232885d2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccdaa0a7608190b10d913e5e3d1b3e |
completed | April 1, 2026, 8:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0665cd43481908287b6d4858d63a1 |
completed | April 4, 2026, 1:16 a.m. |
Created at: March 30, 2026, 7:28 p.m.