Triple
T5566278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ASIFA-Hollywood |
E145885
|
entity |
| Predicate | hasMediaTypeRecognized |
P64827
|
FINISHED |
| Object | feature animation |
—
|
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 animation | Statement: [ASIFA-Hollywood, hasMediaTypeRecognized, feature animation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMediaTypeRecognized Context triple: [ASIFA-Hollywood, hasMediaTypeRecognized, feature animation]
-
A.
hasContentType
Indicates that an entity is associated with or classified by a specific type of content.
-
B.
hasImageType
Indicates that an entity is associated with an image of a particular type or format.
-
C.
hasRightRecognizedIn
Indicates that an entity’s right is formally acknowledged or upheld within a specified context, system, or jurisdiction.
-
D.
canRecognize
Indicates that one entity has the ability to identify or distinguish another entity based on its features or characteristics.
-
E.
hasReadingType
Indicates that an entity is associated with a specific category or mode of reading, such as a particular interpretation, format, or type of reading measurement.
- 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_69c008fdae24819081aa002ad99cd966 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c02034fc3081908920c52a19d462e1 |
completed | March 22, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69c01b12826c8190969a584d0f53aa44 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f4032408190a4f0d2eb21ebd870 |
completed | March 22, 2026, 4:56 p.m. |
Created at: March 22, 2026, 3:36 p.m.