Triple
T16386551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agra metropolitan area |
E397936
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Khandari |
E377844
|
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: Khandari | Statement: [Agra metropolitan area, hasPart, Khandari]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Khandari Context triple: [Agra metropolitan area, hasPart, Khandari]
-
A.
Khandari
chosen
Khandari is a locality in Agra, India, known for its educational institutions and proximity to the historic Sikandra area.
-
B.
Bhandari
Bhandari is a common South Asian surname, particularly found in Nepal and India, associated with various communities and notable public figures.
-
C.
Kalgidhar
Kalgidhar is an honorific epithet of Guru Gobind Singh, emphasizing his revered status as a timeless, divine protector in Sikh tradition.
-
D.
Khadakwasla
Khadakwasla is a suburban area near Pune in Maharashtra, India, known for its lake, dam, and military establishments.
-
E.
Ransingha
Ransingha is a traditional curved brass or copper trumpet used in Himalayan folk music, especially in ceremonial and ritual contexts.
- 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_69d87f2880b48190ae1a9673a3bbef80 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e3263d260081909db9ac6016d5738a |
completed | April 18, 2026, 6:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00356ed47c819085aaf101459dd55c |
completed | May 10, 2026, 7:36 a.m. |
Created at: April 10, 2026, 5:08 a.m.