Triple
T13608408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cameron Tucker |
E325124
|
entity |
| Predicate | professionInSeries |
P80683
|
FINISHED |
| Object | football coach |
—
|
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: football coach | Statement: [Cameron Tucker, professionInSeries, football coach]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionInSeries Context triple: [Cameron Tucker, professionInSeries, football coach]
-
A.
starOccupationInSeries
chosen
Indicates that an individual has a specific occupation or role as a starring character within a particular series.
-
B.
portrayedByProfession
Indicates that an entity is depicted or represented by someone acting in a specified professional capacity.
-
C.
portraysProfession
Indicates that one entity depicts or represents another entity in a specific profession or occupational role.
-
D.
spouseOccupationInSeries
Indicates that a character’s spouse has a particular occupation within the context of a series.
-
E.
developerOfWorkAppearingIn
Indicates that one entity is the creator or developer of a work in which another entity appears or is featured.
- F. None of above.
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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae1b3ee481909bd43ded6227a3e5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:50 p.m.