Triple
T12646095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Farrukhabad |
E302026
|
entity |
| Predicate | localLanguage |
P1252
|
FINISHED |
| Object | Kannauji |
E291133
|
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: Kannauji | Statement: [Farrukhabad, localLanguage, Kannauji]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kannauji Context triple: [Farrukhabad, localLanguage, Kannauji]
-
A.
Kannauj
chosen
Kannauj is a historic town and parliamentary constituency in Uttar Pradesh, India, renowned for its ancient heritage and traditional perfume (attar) industry.
-
B.
Karauli
Karauli is a historic town and pilgrimage center in the Indian state of Rajasthan, known for its ancient temples and distinctive red sandstone architecture.
-
C.
Anupgarh
Anupgarh is a town in the Ganganagar district of Rajasthan, India, known for its agricultural surroundings and proximity to the India–Pakistan border.
-
D.
Partapur
Partapur is a locality in Meerut district of Uttar Pradesh, India, known for its proximity to the Dr. Bhimrao Ambedkar Airstrip and its growing urban and institutional development.
-
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_69d7bdec9f9c8190b4bac675b7588211 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9614cefdc81908cfc4a4d04aa6eda |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6b8c0510081909459662cb91a82b4 |
completed | May 3, 2026, 2:53 a.m. |
Created at: April 9, 2026, 5:17 p.m.