Triple
T20146398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Besnagar |
E491313
|
entity |
| Predicate | ancientNameOf |
P20952
|
FINISHED |
| Object | Vidisha |
—
|
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: Vidisha | Statement: [Besnagar, ancientNameOf, Vidisha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vidisha Context triple: [Besnagar, ancientNameOf, Vidisha]
-
A.
Vidisha
chosen
Vidisha is a historic city in the central Indian state of Madhya Pradesh, known for its ancient Buddhist and Hindu heritage and archaeological sites.
-
B.
Harda
Harda is a town and administrative district headquarters in the central Indian state of Madhya Pradesh, known for its agricultural economy and railway connectivity.
-
C.
Barwani
Barwani is a town in the Indian state of Madhya Pradesh, known for its proximity to the Narmada River and its surrounding hilly, forested landscape.
-
D.
Chhindwara
Chhindwara is a prominent city in central India known for its agricultural produce, tribal culture, and growing industrial and educational hubs within Madhya Pradesh.
-
E.
Anuppur
Anuppur is a town and administrative district headquarters in the central Indian state of Madhya Pradesh, known for its proximity to coal mining areas and natural attractions.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6679e43a48190b3a5da5710b07ff7 |
completed | April 20, 2026, 5:51 p.m. |
Created at: April 11, 2026, 11:33 p.m.