Triple
T9948009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Channel 5 News |
E195253
|
entity |
| Predicate | roleOfTomTucker |
P91302
|
FINISHED |
| Object | news anchor |
—
|
LITERAL 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: news anchor | Statement: [Channel 5 News, roleOfTomTucker, news anchor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleOfTomTucker Context triple: [Channel 5 News, roleOfTomTucker, news anchor]
-
A.
roleOfSteveJordan
Indicates that Steve Jordan holds or performs a particular role or function in relation to another entity or context.
-
B.
roleInFranchiseHistory
Indicates the specific function, position, or contribution an entity has within the historical development or timeline of a franchise.
-
C.
roleAtTampaBayBuccaneers
Indicates that an entity holds or held a specific role or position within the Tampa Bay Buccaneers organization.
-
D.
Levi Todd_role
Indicates that Levi Todd holds or has held a specific role, position, or function in relation to another entity.
-
E.
roleAtNewEnglandPatriots
Indicates the specific role, position, or capacity an entity holds within the New England Patriots organization.
- F. None of above. chosen
Provenance (4 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_69ca82e96a108190932bd1fc4acd73a0 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb659307c81908279adb641ceef86 |
completed | April 2, 2026, 12:20 a.m. |
| PD | Predicate disambiguation | batch_69cd1d97c44081908730071269f07712 |
completed | April 1, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69cd358386f48190833c862b5b8c04b2 |
completed | April 1, 2026, 3:10 p.m. |
Created at: March 30, 2026, 8:45 p.m.