Triple
T34977778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryan Folsey |
E1008727
|
entity |
| Predicate | typeOfEditing |
P114078
|
FINISHED |
| Object | feature film editing |
—
|
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: feature film editing | Statement: [Ryan Folsey, typeOfEditing, feature film editing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfEditing Context triple: [Ryan Folsey, typeOfEditing, feature film editing]
-
A.
editingIs
Indicates that one entity is performing or undergoing the process of editing another entity.
-
B.
editingFor
Indicates that one entity is performing or responsible for editing content on behalf of, or for the benefit of, another entity.
-
C.
editingMode
Indicates that an entity is currently in, or associated with, a state where its content or properties can be modified or edited.
-
D.
editingParadigm
chosen
Indicates the method or style of editing applied to content, such as the structural approach, workflow, or conceptual framework guiding how edits are performed.
-
E.
editedIn
Indicates that an entity was modified, revised, or otherwise altered within a particular context, tool, environment, or time frame.
- 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_69f76dc844a48190881951fffb83d17e |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a017969ff908190a7a1a46b3f5ae362 |
completed | May 11, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_6a017609ff4c8190aba8a1864d39a608 |
completed | May 11, 2026, 6:24 a.m. |
Created at: May 3, 2026, 4:01 p.m.