Triple
T22321377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bardhaman district |
E551794
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Panagarh |
—
|
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: Panagarh | Statement: [Bardhaman district, contains, Panagarh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Panagarh Context triple: [Bardhaman district, contains, Panagarh]
-
A.
Panagarh
chosen
Panagarh is a town in West Bengal, India, known as a key railway and military hub in the Bardhaman district.
-
B.
Surajgarh
Surajgarh is a town in the Jhunjhunu district of Rajasthan, India, known for its historic havelis and traditional Rajasthani architecture.
-
C.
Mahendragarh
Mahendragarh is a town and district headquarters in the northern Indian state of Haryana.
-
D.
Sikandarpur
Sikandarpur is a metro station in the Delhi Metro network that serves the Gurugram area and provides an interchange with the Rapid Metro system.
-
E.
Ganagapur
Ganagapur is a prominent Hindu pilgrimage town in Karnataka, India, revered as a sacred center associated with Lord Dattatreya and the saint Narasimha Saraswati.
- 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_69e11e4776588190abb21e5cea79973f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15764d3a48190af79ce4642b7f563 |
completed | April 29, 2026, 12:57 a.m. |
Created at: April 16, 2026, 8:42 p.m.