Triple
T902532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramayana |
E19476
|
entity |
| Predicate | portraysCharacterAs |
P10301
|
FINISHED |
| Object | Rama as avatar of Vishnu |
—
|
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: Rama as avatar of Vishnu | Statement: [Ramayana, portraysCharacterAs, Rama as avatar of Vishnu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysCharacterAs Context triple: [Ramayana, portraysCharacterAs, Rama as avatar of Vishnu]
-
A.
portraysActorAs
Indicates that one entity depicts or represents an actor in a particular role, character, or manner.
-
B.
portrayedBy
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
-
C.
portrayedByWork
chosen
Indicates that a work (such as a film, book, or artwork) depicts, represents, or portrays a particular entity.
-
D.
characterIn
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
E.
depictsPersonRole
Indicates that an image or representation shows a person in a specific role, function, or capacity.
- 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_69a4939e889c8190ac148b3ac1a7f90b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad56f4c08190a7a5091ff0eb3209 |
completed | March 1, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69a4aa98caec8190bbcc38320090f058 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.