Triple
T7045961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chunar Fort |
E163630
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Mirzapur city |
E161622
|
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: Mirzapur city | Statement: [Chunar Fort, near, Mirzapur city]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mirzapur city Context triple: [Chunar Fort, near, Mirzapur city]
-
A.
Mirzapur district
chosen
Mirzapur district is an administrative district in the southeastern part of Uttar Pradesh, India, known for its carpet industry, temples, and the nearby Vindhyachal pilgrimage site.
-
B.
Madhapur
Madhapur is a major IT and business district in Hyderabad, India, known for its technology parks, corporate offices, and modern urban infrastructure.
-
C.
Damoh
Damoh is a city in central India that serves as the administrative headquarters of Damoh district in the state of Madhya Pradesh.
-
D.
Solapur
Solapur is a prominent city in southwestern Maharashtra, India, known for its textile industry, religious sites, and cultural significance to Marathi-speaking people.
-
E.
Nagar
Nagar is a town in India’s historic Braj region, an area closely associated with the life and legends of Lord Krishna.
- 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_69c6885f598c8190b6b6495c59d8d962 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e238c7a4819095f5ff7283d48da8 |
completed | March 27, 2026, 8:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7b8c5a9fc81909a94e8e6c287b591 |
completed | March 28, 2026, 11:17 a.m. |
Created at: March 27, 2026, 2:37 p.m.