Triple
T22136762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panhala Fort |
E547049
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Kolhapur city |
—
|
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: Kolhapur city | Statement: [Panhala Fort, locatedNear, Kolhapur city]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kolhapur city Context triple: [Panhala Fort, locatedNear, Kolhapur city]
-
A.
Kolhapur
chosen
Kolhapur is a historic city in the Indian state of Maharashtra, known for its rich Maratha heritage, temples, and distinctive Kolhapuri cuisine and leather sandals.
-
B.
Paithan
Paithan is an ancient town in Maharashtra, India, historically significant as a major political and cultural center of the Satavahana dynasty.
-
C.
Malegaon
Malegaon is a major textile and powerloom town in Maharashtra, India, known for its large Muslim population and vibrant weaving industry.
-
D.
Nanded
Nanded is a historic city in the Indian state of Maharashtra, known as an important Sikh pilgrimage center and a major urban hub in the Marathwada region.
-
E.
Bhiwapur
Bhiwapur is a town in Maharashtra, India, known for its chili production and location within the Nagpur district.
- 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_69e11e3a95d88190a3bd80d9471976c3 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129bac764819099ba4896a161ef1c |
completed | April 28, 2026, 9:42 p.m. |
Created at: April 16, 2026, 8:32 p.m.