Triple
T10555729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Schamus |
E249080
|
entity |
| Predicate | hasWrittenOnSubject |
P14097
|
FINISHED |
| Object | film theory |
—
|
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: film theory | Statement: [James Schamus, hasWrittenOnSubject, film theory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWrittenOnSubject Context triple: [James Schamus, hasWrittenOnSubject, film theory]
-
A.
hasWrittenAbout
chosen
Indicates that one entity has authored content or material discussing, analyzing, or referencing another entity.
-
B.
hasWrittenFor
Indicates that one entity has created written content (such as articles, stories, or texts) for or on behalf of another entity, typically a publication, organization, or platform.
-
C.
hasBeenSubjectOf
Indicates that an entity has previously been the focus or target of a particular action, process, or investigation.
-
D.
hasNotableSubject
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
-
E.
areWrittenOn
Indicates that one entity serves as a surface or medium on which another entity is inscribed, recorded, or written.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d52712a9988190bf63e7c47f6e6fc1 |
completed | April 7, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69d518fa0b4081909bffc936d78bd77b |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:34 p.m.