Triple
T21611810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ASA Award |
E533329
|
entity |
| Predicate | hasFictionalReputation |
P58963
|
FINISHED |
| Object | top recognition for artists in Empire universe |
—
|
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: top recognition for artists in Empire universe | Statement: [ASA Award, hasFictionalReputation, top recognition for artists in Empire universe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalReputation Context triple: [ASA Award, hasFictionalReputation, top recognition for artists in Empire universe]
-
A.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
-
B.
hasFictionalScope
Indicates that something pertains to, applies within, or is limited to a fictional or imagined context rather than real-world scope.
-
C.
hasFictionalWork
Indicates that one entity is the creator, owner, or source of a fictional work associated with another entity.
-
D.
hasFictionalProperty
chosen
Indicates that an entity possesses a property, attribute, or characteristic that exists only in a fictional or imaginary context.
-
E.
hasFictionalSpecialization
Indicates that an entity’s area of focus, expertise, or role is within a fictional or imaginative domain rather than a real-world specialization.
- 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_69e0c46411108190bba0d4176dffc9f3 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef3ba79424819094e9ee93c4bbcc0b |
completed | April 27, 2026, 10:34 a.m. |
| PD | Predicate disambiguation | batch_69e69665fe8c8190af7e38785db188b2 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:33 p.m.