Triple
T29332130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhakta Prahlada (Telugu film) |
E743807
|
entity |
| Predicate | portraysAvatar |
P20182
|
FINISHED |
| Object | Narasimha |
—
|
NE NERFINISHED |
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 | Statement: [Bhakta Prahlada (Telugu film), portraysAvatar, Narasimha]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysAvatar Context triple: [Bhakta Prahlada (Telugu film), portraysAvatar, Narasimha]
-
A.
avatarOf
Indicates that one entity serves as the embodiment, representation, or manifested form of another entity.
-
B.
portraysPersonAs
Indicates that one entity represents, depicts, or characterizes another person in a particular way or role.
-
C.
portraysActorAs
Indicates that one entity depicts or represents an actor in a particular role, character, or manner.
-
D.
avatar
chosen
Indicates that one entity serves as a representation, embodiment, or proxy of another entity, often in a different form or medium.
-
E.
portrayedByCharacterType
Indicates that an entity is depicted or represented by a character of a specified type (e.g., hero, villain, sidekick) in a narrative or media work.
- 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_69f09125f784819080f4e9fce9fe624f |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69fd0b92f42881908cd77e3f058adcc2 |
completed | May 7, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fd0a3d68d4819094d92040f7c48d7c |
completed | May 7, 2026, 9:55 p.m. |
Created at: April 28, 2026, 1:29 p.m.