Triple
T11202070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chirang district |
E265064
|
entity |
| Predicate | administrativeHeadquarters |
P62
|
FINISHED |
| Object | Kajalgaon |
E915899
|
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: Kajalgaon | Statement: [Chirang district, administrativeHeadquarters, Kajalgaon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kajalgaon Context triple: [Chirang district, administrativeHeadquarters, Kajalgaon]
-
A.
Kajalgaon
chosen
Kajalgaon is a town in the Indian state of Assam that serves as the administrative center of Chirang district.
-
B.
Kahalgaon
Kahalgaon is a town in the Bhagalpur district of Bihar, India, known for its thermal power station and proximity to the historic Vikramshila university site.
-
C.
Karanpur
Karanpur is a town located in the Ganganagar district of the northern Indian state of Rajasthan.
-
D.
Bhadgaon
Bhadgaon is another name for Bhaktapur, a historic Newar city in the Kathmandu Valley of Nepal renowned for its well-preserved medieval architecture, art, and culture.
-
E.
Daryapur
Daryapur is a town in the Amravati district of Maharashtra, India, known for its agricultural economy and regional market activities.
- 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_69d6aa9eb9248190b20211772621b4bc |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8c36c188190bfa4d5f8e6cbbbea |
completed | April 9, 2026, 5:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e509dd91288190beefaaa451d692ae |
completed | April 19, 2026, 4:59 p.m. |
Created at: April 8, 2026, 9:29 p.m.