Triple
T22368273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pfister |
E552968
|
entity |
| Predicate | usedInFieldByBearers |
P34346
|
FINISHED |
| Object | 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: film | Statement: [Pfister, usedInFieldByBearers, film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInFieldByBearers Context triple: [Pfister, usedInFieldByBearers, film]
-
A.
hasNotableFieldOfBearers
Indicates that the entities share a significant or distinguished area of activity, expertise, or achievement associated with their bearers.
-
B.
associatedWithStateThroughBearers
Indicates a relationship where an entity is linked to a state indirectly via intermediary bearers (such as organizations, agents, or instruments) that connect it to that state.
-
C.
typicalBearers
chosen
Indicates that certain entities are the usual or characteristic holders, users, or possessors of a given property, role, or attribute.
-
D.
hasAlternativeBearers
Indicates that an entity can be carried, represented, or borne by more than one possible bearer or carrier as alternatives.
-
E.
hasMultipleBearers
Indicates that a single item, attribute, or role is associated with more than one bearer or holder simultaneously.
- 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_69e11e4affcc8190ba7c27d29062558d |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1580229688190a6e5e02b484033f7 |
completed | April 29, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69e73011e6388190a05edf137f488441 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:44 p.m.