Triple
T1436567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vaishnavism |
E30572
|
entity |
| Predicate | honorsAvatar |
P2354
|
FINISHED |
| Object | Varaha |
E110823
|
NE 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: Varaha | Statement: [Vaishnavism, honorsAvatar, Varaha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Varaha Context triple: [Vaishnavism, honorsAvatar, Varaha]
-
A.
Varaha
chosen
Varaha is the boar incarnation of the Hindu god Vishnu, revered for rescuing the earth from cosmic waters and defeating the demon Hiranyaksha.
-
B.
Shabara
Shabara was an early Indian philosopher and commentator best known for his influential exegesis on the Purva Mimamsa school of Hindu philosophy.
-
C.
Harauti
Harauti is an Indo-Aryan dialect of the Rajasthani language spoken primarily in the Hadoti region of Rajasthan, India.
-
D.
Krakhuna
Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
-
E.
Vivarais
Vivarais is a historical region in south-central France, known for its rugged landscapes, part of the broader Massif Central, and its traditional rural culture.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a498fc69ec8190b61722bd4b67c4d2 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c9df014081908a6e2f41ba012ecc |
completed | March 1, 2026, 11:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad2328670c819087a2d8b047b67ee8 |
completed | March 8, 2026, 7:20 a.m. |
Created at: March 1, 2026, 8 p.m.