Triple
T1410488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mirzapur |
E31791
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Uttar Pradesh |
E10722
|
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: Uttar Pradesh | Statement: [Mirzapur, locatedIn, Uttar Pradesh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uttar Pradesh Context triple: [Mirzapur, locatedIn, Uttar Pradesh]
-
A.
Uttar Pradesh
chosen
Uttar Pradesh is a populous northern Indian state known for its political influence, rich cultural and religious heritage, and historic cities such as Varanasi and Agra.
-
B.
Madhya Pradesh
Madhya Pradesh is a large central Indian state known for its historical cities, diverse tribal cultures, and significant forested and wildlife areas including several major national parks.
-
C.
Haryana
Haryana is a northern Indian state known for its significant agricultural output, rapid industrial growth, and proximity to the national capital, New Delhi.
-
D.
Rajasthan
Rajasthan is a northwestern Indian state known for its vast Thar Desert, historic Rajput forts and palaces, and rich cultural heritage.
-
E.
Bihar
Bihar is a populous state in eastern India known for its rich historical heritage, including ancient centers of learning like Nalanda and significant sites in Buddhist history.
- 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_69a49918e1f88190ba610f9dc8114578 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3e0bfd08190a50820bc7585c28f |
completed | March 1, 2026, 10:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae26de62d48190849540112614ccce |
completed | March 9, 2026, 1:48 a.m. |
Created at: March 1, 2026, 7:59 p.m.