Triple
T1916065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bundelkhand |
E40019
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Tikamgarh |
E143463
|
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: Tikamgarh | Statement: [Bundelkhand, hasCity, Tikamgarh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tikamgarh Context triple: [Bundelkhand, hasCity, Tikamgarh]
-
A.
Tikamgarh
chosen
Tikamgarh is a town and administrative center in central India, known for its historical forts and temples in the state of Madhya Pradesh.
-
B.
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.
-
C.
Alirajpur
Alirajpur is a town and district headquarters in western Madhya Pradesh, India, known for its predominantly tribal population and vibrant indigenous culture.
-
D.
Narsinghpur
Narsinghpur is a city and administrative center in central India known for its agricultural economy, particularly sugarcane and pulses, within the state of Madhya Pradesh.
-
E.
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.
- 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_69a8864298748190a2f2fd34f7ef8d77 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb1e517e8819086e4bf5a305aeb25 |
completed | March 7, 2026, 5:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adf3da81308190a49844a8ac2997da |
completed | March 8, 2026, 10:10 p.m. |
Created at: March 4, 2026, 7:35 p.m.