Triple
T20479619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ahuna |
E502416
|
entity |
| Predicate | linkedConcept |
P37
|
FINISHED |
| Object | Asha |
—
|
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: Asha | Statement: [Ahuna, linkedConcept, Asha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asha Context triple: [Ahuna, linkedConcept, Asha]
-
A.
Asha
Asha is the given name of legendary Indian playback singer Asha Bhosle, renowned for her versatile and prolific contributions to Hindi cinema music.
-
B.
Asha
Asha is a line of budget-friendly Nokia mobile phones designed to offer smartphone-like features to emerging markets.
-
C.
Asha
chosen
Asha is a central Zoroastrian and Iranian mythological concept representing truth, cosmic order, and righteousness that upholds the moral and natural structure of the universe.
-
D.
Asha
Asha is a small industrial town in the western part of Chelyabinsk Oblast in Russia, known for its metallurgical and machine-building industries.
-
E.
Ascha
Ascha is a small municipality in the district of Straubing-Bogen in Lower Bavaria, Germany.
- 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_69e0b4af32848190aea80682b44d5d6e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69b55d7a881909dfe3ea0e74b742b |
completed | April 20, 2026, 9:32 p.m. |
Created at: April 16, 2026, 11:34 a.m.