Triple
T7977729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bob Hoskins as Mr. Fezziwig |
E185486
|
entity |
| Predicate | portrayalFormat |
P80112
|
FINISHED |
| Object | feature 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: feature film | Statement: [Bob Hoskins as Mr. Fezziwig, portrayalFormat, feature film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayalFormat Context triple: [Bob Hoskins as Mr. Fezziwig, portrayalFormat, feature film]
-
A.
portrayalFeature
Indicates that one entity serves as a characteristic, aspect, or attribute highlighted in the depiction or representation of another entity.
-
B.
portrayalRecognition
Indicates that one entity recognizes or identifies another entity as a portrayal or representation of a particular subject or character.
-
C.
portrayalLanguage
Indicates the language in which something is depicted, represented, or expressed.
-
D.
portrayalIntendedAs
Indicates that one entity is meant to represent, depict, or stand in for another entity in an intentional portrayal.
-
E.
portrayalStart
Indicates the point in time or sequence at which a particular portrayal or depiction of something begins.
- 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_69ca829851908190b4e03829353ee7c3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3bf716508190b4245bd5d89ae8c4 |
completed | March 31, 2026, 3:13 a.m. |
| PD | Predicate disambiguation | batch_69cb047a8e4c81909b79e0f0bf56440c |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14bbbacc81909c6cf8ec35314bbb |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:14 p.m.