Triple
T15738867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Varuna |
E381549
|
entity |
| Predicate | consort |
P13
|
FINISHED |
| Object | Varuni |
E448892
|
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: Varuni | Statement: [Varuna, consort, Varuni]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Varuni Context triple: [Varuna, consort, Varuni]
-
A.
Varuni
chosen
Varuni is a Hindu goddess associated with wine and divine intoxication, revered as the consort of the Vedic sea god Varuna.
-
B.
Kala Pani
Kala Pani is the infamous British-era colonial prison in the Andaman and Nicobar Islands, known for its harsh conditions and use to exile Indian freedom fighters.
-
C.
Vaidehi
Vaidehi is an epithet of Sita, the revered heroine of the Hindu epic Ramayana and wife of Lord Rama.
-
D.
Sudevi
Sudevi is one of the eight principal gopi companions of Radha and Krishna in Vaishnava tradition, revered for her intimate devotional service in the sacred pastimes of Vrindavan.
-
E.
Neera
Neera is a key iguanodon character in Disney's 2000 animated film "Dinosaur," serving as the strong-willed female lead and love interest of the protagonist, Aladar.
- 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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04fd816308190a297986ee7e5554c |
completed | April 16, 2026, 2:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff830336248190a8bbd8153dd95daa |
completed | May 9, 2026, 6:54 p.m. |
Created at: April 10, 2026, 4:46 a.m.