Triple
T15008650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kumail Nanjiani |
E377777
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Nanjiani |
E377777
|
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: Nanjiani | Statement: [Kumail Nanjiani, familyName, Nanjiani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nanjiani Context triple: [Kumail Nanjiani, familyName, Nanjiani]
-
A.
Nanjiani
chosen
Nanjiani is the surname of Kumail Nanjiani, a Pakistani-American comedian, actor, and writer known for his work in stand-up, film, and television.
-
B.
Nabha
Nabha is a historic town in the Indian state of Punjab, known for its former princely state status and cultural heritage.
-
C.
Nandy
Nandy is a Tanzanian singer and songwriter known for her Bongo Flava hits and collaborations with prominent East African artists.
-
D.
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.
-
E.
Rajani
Rajani is a Bengali novel by renowned 19th-century writer Bankim Chandra Chattopadhyay, noted for its exploration of social and emotional themes in colonial India.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded73348d4819091d9e7f1b0fed822 |
completed | April 15, 2026, 12:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9dce8240819097efddb43b79ad4b |
completed | May 9, 2026, 2:37 a.m. |
Created at: April 10, 2026, 2:55 a.m.