Triple
T6020853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patsy Barton |
E134058
|
entity |
| Predicate | workTypeOfAppearance |
P1366
|
FINISHED |
| Object | musical 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: musical film | Statement: [Patsy Barton, workTypeOfAppearance, musical film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workTypeOfAppearance Context triple: [Patsy Barton, workTypeOfAppearance, musical film]
-
A.
typeOfWork
chosen
Indicates the kind or category of work associated with or performed by an entity.
-
B.
allegedAppearanceType
Indicates the type or nature of an appearance that is claimed or reported to have occurred, without confirming that the appearance actually took place.
-
C.
workTypeContributedTo
Indicates that an entity contributed to the creation, development, or production of a particular type of work.
-
D.
workCharacterType
Indicates that a work involves or features a character of a specified type or role.
-
E.
employmentType
Indicates the specific kind or category of employment relationship that exists between an individual and an employer (e.g., full-time, part-time, contract).
- 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_69c008742a5c8190b9cb9c2787a3d8b3 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04fba86a48190984e95d5adf7c7f1 |
completed | March 22, 2026, 8:23 p.m. |
| PD | Predicate disambiguation | batch_69c049e75b3881908be106fbcf8c68d4 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:07 p.m.