Triple
T26893175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | মেঘনাদবধ কাব্য |
E677829
|
entity |
| Predicate | portraysAsAntagonist |
P42601
|
FINISHED |
| Object | রাম |
—
|
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: রাম | Statement: [মেঘনাদবধ কাব্য, portraysAsAntagonist, রাম]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysAsAntagonist Context triple: [মেঘনাদবধ কাব্য, portraysAsAntagonist, রাম]
-
A.
portraysAdversary
chosen
Indicates that one entity depicts or represents another entity as an opponent, enemy, or rival.
-
B.
antagonistActorRole
Indicates that an actor plays the role of an antagonist in a given work or context.
-
C.
hasAntagonisticProtagonist
Indicates that the work features a main character who opposes or undermines the typical heroic or moral expectations of a traditional protagonist.
-
D.
mainAntagonistPortrayedBy
Indicates that the person is the primary actor who plays the main antagonist character in a work.
-
E.
antagonistOf
Indicates a relationship where one entity actively opposes, conflicts with, or serves as an adversary to another.
- 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_69eee9befee48190a26f214faa867be7 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f757898fe48190b124dc7301672623 |
completed | May 3, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_69f754c484348190948d2a04ff228fb1 |
completed | May 3, 2026, 1:59 p.m. |
Created at: April 27, 2026, 5:46 a.m.