Triple
T20930030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maratha region |
E515445
|
entity |
| Predicate | hasSubregion |
P285
|
FINISHED |
| Object | Desh |
—
|
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: Desh | Statement: [Maratha region, hasSubregion, Desh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Desh Context triple: [Maratha region, hasSubregion, Desh]
-
A.
Desh
chosen
Desh is a historical region in western Maharashtra, India, known for its cultural significance and role in the Maratha heartland.
-
B.
Desh
Desh is a critically acclaimed solo dance-theatre work by British-Bangladeshi choreographer Akram Khan that explores identity, memory, and homeland.
-
C.
Desiya
Desiya is a regional dialect spoken in parts of Odisha, India, influenced by Odia and neighboring tribal and Indo-Aryan languages.
-
D.
Negara
Negara is a town in western Bali, Indonesia, known as an administrative and commercial center in the Jembrana Regency.
-
E.
Deesa
Deesa is a town in the Banaskantha district of Gujarat, India, known historically as a former princely state and for its nearby military air base.
- 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_69e0b4fb431c8190b9d40e6a72f0cc87 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6f6545f8c81908a8c2f0e8d7b060e |
completed | April 21, 2026, 4 a.m. |
Created at: April 16, 2026, 12:49 p.m.