Triple
T11102532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kapoor |
E262548
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Kapur |
E262548
|
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: Kapur | Statement: [Kapoor, hasVariant, Kapur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kapur Context triple: [Kapoor, hasVariant, Kapur]
-
A.
Kapoor (Kapur)
chosen
Kapoor (Kapur) is an Indian surname and family name commonly associated with Punjabi Khatris and several prominent figures in Indian cinema and public life.
-
B.
Malkapur
Malkapur is a town and municipal council in Maharashtra, India, known as a commercial and transport hub within Buldhana district.
-
C.
Kathiawari
Kathiawari is a regional dialect of Gujarati spoken primarily in the Saurashtra (Kathiawar) peninsula of western India, known for its distinct phonetic and lexical features.
-
D.
Kasarani
Kasarani is a residential and commercial suburb in northeastern Nairobi, Kenya, known for hosting major sports and educational facilities.
-
E.
Jwalapur
Jwalapur is a prominent suburban town and commercial hub near Haridwar in the Indian state of Uttarakhand.
- 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79a2c30a481908c45020c37caebe4 |
completed | April 9, 2026, 12:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3e7f9b46881909761ed448fa5ce6e |
completed | April 18, 2026, 8:22 p.m. |
Created at: April 8, 2026, 9:27 p.m.