Triple
T30872717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Actor for Broadcast News |
E786385
|
entity |
| Predicate | roleOccupation |
P2374
|
FINISHED |
| Object | television 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: television news anchor | Statement: [Academy Award for Best Actor for Broadcast News, roleOccupation, television news anchor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleOccupation Context triple: [Academy Award for Best Actor for Broadcast News, roleOccupation, television news anchor]
-
A.
occupationAsPersona
Indicates that an entity holds or performs a particular occupation specifically in the role or persona of another characterized identity.
-
B.
subjectOccupation
chosen
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
C.
roleDuringOccupation
Indicates the specific role or position an entity held during a particular occupation or period of control.
-
D.
sonOccupation
Indicates that a specified occupation is the job or professional role held by a person's son.
-
E.
employedRole
Indicates that an entity holds or performs a specific role or position within an employment or work context.
- 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_69f224b9df2c819086f55f8bcf7f382e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: April 29, 2026, 8:48 p.m.