Triple
T5647148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parashurama |
E124412
|
entity |
| Predicate | alternateName |
P39
|
FINISHED |
| Object | Parashurama Avatar |
E124412
|
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: Parashurama Avatar | Statement: [Parashurama, alternateName, Parashurama Avatar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Parashurama Avatar Context triple: [Parashurama, alternateName, Parashurama Avatar]
-
A.
Parashurama
chosen
Parashurama is the warrior-sage incarnation of the Hindu god Vishnu, famed for wielding an axe and for his role in purging corrupt Kshatriya rulers.
-
B.
Narasimha
Narasimha is the fierce man-lion incarnation of the Hindu god Vishnu, known for destroying the demon king Hiranyakashipu to protect his devotee Prahlada.
-
C.
Anjaneya
Anjaneya is another name for the Hindu deity Hanuman, revered as a symbol of strength, devotion, and selfless service.
-
D.
Pradyumna
Pradyumna is a prominent figure in Hindu mythology, known as the son of Krishna and Rukmini and considered an incarnation of the love god Kamadeva.
-
E.
Sesha Vahana
Sesha Vahana is the divine serpent mount of Lord Vishnu, prominently featured in Hindu temple festivals and iconography.
- 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_69c00825df388190a58742fa9b1aa33d |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022abf0108190b10b3a9fe1688bf9 |
completed | March 22, 2026, 5:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04d88bbf08190b32d1ad157e28fe4 |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 3:41 p.m.