Triple
T20598780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Disney Legend |
E506117
|
entity |
| Predicate | includesCategories |
P82611
|
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: [Disney Legend, includesCategories, film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesCategories Context triple: [Disney Legend, includesCategories, film]
-
A.
containsCategory
Indicates that one entity includes or encompasses a specific category as part of its classification or organizational structure.
-
B.
hasCategories
chosen
Indicates that an entity is associated with one or more categories that classify or group it.
-
C.
hasCategoryWithin
Indicates that one category is contained within or is a subcategory of another category.
-
D.
classificationIncludes
Indicates that a broader classification category encompasses or contains a specified subclass, member, or element within its scope.
-
E.
usesCategorySystem
Indicates that one entity organizes or classifies things according to a particular category system defined by another entity.
- 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_69e0b4ba6ae88190af871e1f9522c704 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aa1e251c8190926dafe1402eb63c |
completed | April 20, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69e59fffe1748190825e4eaa90340631 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:40 a.m.