Triple
T499055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tariq Anwar |
E10358
|
entity |
| Predicate | workedOnGenre |
P14417
|
FINISHED |
| Object | drama film |
—
|
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: drama film | Statement: [Tariq Anwar, workedOnGenre, drama film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workedOnGenre Context triple: [Tariq Anwar, workedOnGenre, drama film]
-
A.
notableWorkGenre
Indicates that a particular work is recognized as notable for an entity and specifies the genre to which that work belongs.
-
B.
workedAs
Indicates that an entity held a particular job, role, or position, performing work in that capacity.
-
C.
workedUnder
Indicates that one entity was hierarchically subordinate to and performed work under the supervision or authority of another entity.
-
D.
workBy
Indicates that a work (such as a creation, product, or result) is produced, authored, or created by a particular agent or entity.
-
E.
influencedWork
Indicates that one work has had a significant impact on the creation, style, content, or development of another work.
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f119b14c8190a5a6b119579c2682 |
completed | Feb. 28, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69a2edfa87cc8190a77c726a5a55b7d9 |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eebbd70481908b462296671de67b |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.