Triple
T21428585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Twinkle Khanna |
E528624
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Khanna |
—
|
NE NERFINISHED |
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: Khanna | Statement: [Twinkle Khanna, familyName, Khanna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Khanna Context triple: [Twinkle Khanna, familyName, Khanna]
-
A.
Khanna
Khanna is a prominent town in the Indian state of Punjab, known especially as a major grain market and commercial hub in the region.
-
B.
Lakhpat
Lakhpat is a historic fortified town in the Kutch district of Gujarat, India, known for its massive walls and once-thriving port on the Arabian Sea.
-
C.
Karnal
Karnal is a historic city in the Indian state of Haryana, known for its agricultural significance and strategic location along the Grand Trunk Road between Delhi and Chandigarh.
-
D.
Mehra
chosen
Mehra is an Indian surname commonly associated with North Indian communities and notably borne by figures such as filmmaker Rakeysh Omprakash Mehra.
-
E.
Kadipur
Kadipur is a town in the Sultanpur district of Uttar Pradesh, India, functioning as a local administrative and commercial center for the surrounding rural area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c455f3688190810bc96365791b0f |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee813db52c8190ac933bc6ec4dbf77 |
completed | April 26, 2026, 9:18 p.m. |
Created at: April 16, 2026, 5:49 p.m.