Triple
T902909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arjuna |
E19483
|
entity |
| Predicate | roleInBhagavadGita |
P9564
|
FINISHED |
| Object | primary recipient of Krishna's teachings |
—
|
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: primary recipient of Krishna's teachings | Statement: [Arjuna, roleInBhagavadGita, primary recipient of Krishna's teachings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInBhagavadGita Context triple: [Arjuna, roleInBhagavadGita, primary recipient of Krishna's teachings]
-
A.
roleInTheology
Indicates the specific function, position, or significance an entity holds within a theological system, doctrine, or belief framework.
-
B.
roleInWarAndPeace
Indicates that an entity has a specific role or function within the context of the War and Peace conflict or narrative.
-
C.
roleInText
Indicates that an entity participates in a text with a specific function or capacity (e.g., author, editor, character).
-
D.
mythologicalRole
Indicates the specific function, duty, or status an entity holds within a mythological or legendary context.
-
E.
roleInDialogue
chosen
Indicates that an entity participates in a dialogue with a specific conversational role (e.g., speaker, listener, moderator) relative to other participants.
- 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.