Triple
T2613679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goldwyn Pictures |
E58834
|
entity |
| Predicate | operationalForm |
P41427
|
FINISHED |
| Object | corporation |
—
|
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: corporation | Statement: [Goldwyn Pictures, operationalForm, corporation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operationalForm Context triple: [Goldwyn Pictures, operationalForm, corporation]
-
A.
originalForm
Indicates that one entity is the earlier, source, or initial version from which another entity is derived or transformed.
-
B.
standardFormUsedIn
Indicates that a particular standard form is employed or applied within a given context, process, or system.
-
C.
standardFormulation
Indicates that something is expressed or represented in a conventional, officially accepted, or commonly used form or version.
-
D.
visualForm
Indicates the visual appearance, shape, or structural pattern that characterizes how something looks.
-
E.
alternativeForm
Indicates that one entity is an alternative version, variant, or representation of another entity.
- F. None of above. chosen
Provenance (4 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_69ab4ac444dc819099614e534dd6021f |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd89325308190985598373eb0d296 |
completed | March 7, 2026, 7:49 a.m. |
| PD | Predicate disambiguation | batch_69abd80cd7fc81909e9696db2919129f |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd891bcd481909af5340a64ff69f9 |
completed | March 7, 2026, 7:49 a.m. |
Created at: March 6, 2026, 9:50 p.m.