Triple
T7296302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nadia district |
E164529
|
entity |
| Predicate | headquarters |
P62
|
FINISHED |
| Object | Krishnanagar |
E182525
|
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: Krishnanagar | Statement: [Nadia district, headquarters, Krishnanagar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Krishnanagar Context triple: [Nadia district, headquarters, Krishnanagar]
-
A.
Krishnanagar
chosen
Krishnanagar is a historic town in eastern India known for its cultural heritage, temples, and traditional clay artistry.
-
B.
Baranagar
Baranagar is a densely populated suburban city in the northern part of Kolkata, India, known for its industrial areas, educational institutions, and cultural heritage.
-
C.
Muktainagar
Muktainagar is a town in the Jalgaon district of Maharashtra, India, known primarily as an agricultural and trading center in the region.
-
D.
Raiganj
Raiganj is a town in northern West Bengal, India, known as the headquarters of Uttar Dinajpur district and for its nearby Raiganj Wildlife Sanctuary.
-
E.
Chalisgaon
Chalisgaon is a town in the Indian state of Maharashtra known for its railway junction and proximity to historical and religious sites.
- 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_69c6887a499881909dd23341399c59d8 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6eb8d0c6c8190b32cd08b9a5d96cc |
completed | March 27, 2026, 8:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c84ede6c4c8190ad7ade8ce3bbc35e |
completed | March 28, 2026, 9:57 p.m. |
Created at: March 27, 2026, 3 p.m.