Triple
T8921671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hinganghat taluka |
E212432
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Hinganghat |
E212425
|
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: Hinganghat | Statement: [Hinganghat taluka, containsTown, Hinganghat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hinganghat Context triple: [Hinganghat taluka, containsTown, Hinganghat]
-
A.
Hinganghat
chosen
Hinganghat is a town in the Indian state of Maharashtra known for its textile industry and cotton trading.
-
B.
Ghoghardiha
Ghoghardiha is a town located in the Madhubani district of the Indian state of Bihar.
-
C.
Bhatapara
Bhatapara is a regional dialect of the Chhattisgarhi language spoken in and around the town of Bhatapara in the Indian state of Chhattisgarh.
-
D.
Nalhati
Nalhati is a town in the Birbhum district of West Bengal, India, known for its religious significance and regional marketplace.
-
E.
Bhailsa
Bhailsa is the former historical name of Vidisha, an ancient city in the central Indian state of Madhya Pradesh known for its rich archaeological and cultural heritage.
- 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_69ca839481d48190b42b037e0d0f636c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc665024f081909515e02e5f5b2221 |
completed | April 1, 2026, 12:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc1d31f84819098c34c2589949c6e |
completed | April 3, 2026, 1:34 p.m. |
Created at: March 30, 2026, 6:56 p.m.