Triple
T22675677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parbhani district |
E560338
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Parbhani |
—
|
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: Parbhani | Statement: [Parbhani district, hasCapital, Parbhani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Parbhani Context triple: [Parbhani district, hasCapital, Parbhani]
-
A.
Parbhani
chosen
Parbhani is a significant city in the Marathwada region of Maharashtra, India, known as an important commercial and educational center.
-
B.
Baramati
Baramati is a town in the Pune district of Maharashtra, India, known as an agricultural and industrial hub with historical and political significance.
-
C.
Bhoranj
Bhoranj is a town in the Hamirpur district of Himachal Pradesh, India, known as a local administrative and commercial center for surrounding rural areas.
-
D.
Bhawanipatna
Bhawanipatna is a town in the Indian state of Odisha known as an administrative and commercial center of the Kalahandi region.
-
E.
Jwalapur
Jwalapur is a prominent suburban town and commercial hub near Haridwar in the Indian state of Uttarakhand.
- 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_69e2454bfd00819099115715a22cb057 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17823bd1881908958b0a8ba59e199 |
completed | April 29, 2026, 3:16 a.m. |
Created at: April 17, 2026, 3:11 p.m.