Triple
T5583041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Narasimha |
E146684
|
entity |
| Predicate | avatarType |
P57132
|
FINISHED |
| Object | Narasimha avatar |
—
|
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: Narasimha avatar | Statement: [Narasimha, avatarType, Narasimha avatar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: avatarType Context triple: [Narasimha, avatarType, Narasimha avatar]
-
A.
avatar
Indicates that one entity serves as a representation, embodiment, or proxy of another entity, often in a different form or medium.
-
B.
avatarOf
chosen
Indicates that one entity serves as the embodiment, representation, or manifested form of another entity.
-
C.
faceType
Indicates the specific shape or structural category of a face that an entity possesses or is characterized by.
-
D.
adaptationAppearance
Indicates that one entity appears or is depicted in an adaptation of another entity (such as a work being represented in a derived or reinterpreted version).
-
E.
costumeType
Indicates the specific kind or category of costume associated with an 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_69c0090287a08190b4098411effe970c |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0208333f08190bf0049b6bdd280f5 |
completed | March 22, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69c01b16b9bc8190ab0b945507d90e05 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:37 p.m.