Triple
T37383275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terence Nance |
E928493
|
entity |
| Predicate | hasPartInHisCreativePractice |
P108084
|
FINISHED |
| Object | animation |
—
|
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: animation | Statement: [Terence Nance, hasPartInHisCreativePractice, animation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPartInHisCreativePractice Context triple: [Terence Nance, hasPartInHisCreativePractice, animation]
-
A.
hasArtisticWorks
Indicates that an entity possesses, is associated with, or is the creator of one or more artistic works.
-
B.
hasCreatedWorksFor
Indicates that one entity has produced or created works (such as art, documents, or products) on behalf of or for the benefit of another entity.
-
C.
hasArtisticActivity
chosen
Indicates that an entity engages in, participates in, or is associated with an artistic activity or creative practice.
-
D.
hasArtisticDiscipline
Indicates that one entity practices, specializes in, or is associated with a particular artistic discipline or field.
-
E.
hasPartInCreativeOutput
Indicates that an entity contributed a component, role, or involvement to the creation or production of a particular creative work.
- 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_69f76eb9e66881908534cf22d04c3b5a |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a005247dba08190acadf962bcefe4a0 |
completed | May 10, 2026, 9:39 a.m. |
| PD | Predicate disambiguation | batch_6a00519029848190a234358dfba45084 |
completed | May 10, 2026, 9:36 a.m. |
Created at: May 3, 2026, 4:16 p.m.