Triple
T19595249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Lanka |
E470332
|
entity |
| Predicate | hasAllyOfProtagonist |
P30915
|
FINISHED |
| Object | Vibhishana |
—
|
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: Vibhishana | Statement: [Battle of Lanka, hasAllyOfProtagonist, Vibhishana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vibhishana Context triple: [Battle of Lanka, hasAllyOfProtagonist, Vibhishana]
-
A.
Vibhishana
chosen
Vibhishana is a virtuous rakshasa prince in the Hindu epic Ramayana, known for abandoning his brother Ravana to ally with Rama and uphold dharma.
-
B.
Sugriva
Sugriva is the exiled monkey king in the Hindu epic Ramayana who allies with Rama to defeat the demon king Ravana and reclaim his own throne.
-
C.
Rama
Rama is a character in John Steinbeck’s novel "To a God Unknown," representing mystical and spiritual elements within the story’s exploration of land, faith, and destiny.
-
D.
Rama
Rama is a river in Bosnia and Herzegovina that flows through mountainous terrain before joining the Neretva River.
-
E.
Rama
Rama is a Palestinian village in the Galilee region of northern Israel, historically notable for its capture during the 1948 Arab–Israeli War.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640793cd88190b9b84491bfb2493f |
completed | April 20, 2026, 3:04 p.m. |
Created at: April 10, 2026, 1:43 p.m.