Triple
T7852244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buldhana district |
E182083
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Buldhana |
E182083
|
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: Buldhana | Statement: [Buldhana district, hasCity, Buldhana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buldhana Context triple: [Buldhana district, hasCity, Buldhana]
-
A.
Buldhana
chosen
Buldhana is a district in the Indian state of Maharashtra known for its Marathi-speaking population and use of the Varhadi dialect.
-
B.
Hingoli
Hingoli is a city in the Indian state of Maharashtra, known as an administrative and commercial center in the Marathwada region.
-
C.
Ratnagiri
Ratnagiri is a coastal city in Maharashtra, India, known for its Alphonso mangoes, historic forts, and scenic beaches along the Konkan coast.
-
D.
Bhusawal
Bhusawal is a major railway and commercial city in Maharashtra, India, known for its large railway junction and banana-growing region.
-
E.
Sangli
Sangli is a city in the Indian state of Maharashtra known for its fertile agricultural surroundings and prominence in sugar and turmeric production.
- 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_69ca82869ee08190b8f9040dbc2c0467 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb18ec48548190960bd564a60effa8 |
completed | March 31, 2026, 12:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbdf21add88190bc07d3164e940116 |
completed | March 31, 2026, 2:50 p.m. |
Created at: March 30, 2026, 4:51 p.m.