Triple
T14787876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sitapur district |
E347574
|
entity |
| Predicate | headquarters |
P62
|
FINISHED |
| Object | Sitapur |
E1036645
|
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: Sitapur | Statement: [Sitapur district, headquarters, Sitapur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sitapur Context triple: [Sitapur district, headquarters, Sitapur]
-
A.
Sitapur
chosen
Sitapur is a prominent city and administrative center in the Indian state of Uttar Pradesh, known for its agricultural trade and regional connectivity.
-
B.
Alirajpur
Alirajpur is a town and district headquarters in western Madhya Pradesh, India, known for its predominantly tribal population and vibrant indigenous culture.
-
C.
Chandanpura
Chandanpura is a locality in Chittagong, Bangladesh, known for its historic architecture and urban commercial activity.
-
D.
Shivpuri
Shivpuri is a historic town and former princely state in central India, known for its forests, wildlife sanctuaries, and royal palaces.
-
E.
Sohagpur
Sohagpur is a town in the Narmadapuram district of Madhya Pradesh, India, known as a local commercial center and access point to nearby forested and wildlife areas.
- 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decaa083e481908336d58d026eec32 |
completed | April 14, 2026, 11:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe24b9e8a08190bc736ac207b77324 |
completed | May 8, 2026, 6 p.m. |
Created at: April 10, 2026, 1:31 a.m.