Triple
T21591578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Derek Ceeley |
E532792
|
entity |
| Predicate | workAppearanceType |
P34961
|
FINISHED |
| Object | animated adventure 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: animated adventure film | Statement: [Derek Ceeley, workAppearanceType, animated adventure film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workAppearanceType Context triple: [Derek Ceeley, workAppearanceType, animated adventure film]
-
A.
workAttribute
chosen
Indicates that a particular characteristic, quality, or property is associated with a specific work or piece of work.
-
B.
hasWorkStyle
Indicates the type or manner in which an entity typically performs work or carries out tasks.
-
C.
workMode
Indicates the manner, configuration, or operational state in which an entity performs its work or function.
-
D.
appliesToWork
Indicates that something (such as a rule, policy, condition, or attribute) is relevant to, governs, or is in effect for a particular piece of work or work-related activity.
-
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_69e0c46251648190876f0427cf2d321b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eefaddc8508190950b31e2df865ad1 |
completed | April 27, 2026, 5:57 a.m. |
| PD | Predicate disambiguation | batch_69e632109d048190b4ac3f14fe48d1a0 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:32 p.m.