Triple
T21511977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Problem with Jon Stewart |
E530746
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Brinda Adhikari |
—
|
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: Brinda Adhikari | Statement: [The Problem with Jon Stewart, executiveProducer, Brinda Adhikari]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brinda Adhikari Context triple: [The Problem with Jon Stewart, executiveProducer, Brinda Adhikari]
-
A.
Brinda Adhikari
chosen
Brinda Adhikari is a television news and talk-show producer best known for serving as executive producer of Jon Stewart’s current affairs series "The Problem with Jon Stewart."
-
B.
Sutapa Sikdar
Sutapa Sikdar is an Indian dialogue and screenplay writer best known as the wife of acclaimed actor Irrfan Khan.
-
C.
Anuradha Banerjee
Anuradha Banerjee is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Banerjee.
-
D.
Sutapa Basu
Sutapa Basu is an Indian author and poet known for her historical fiction and contemporary novels.
-
E.
Rangita Pritish Nandy
Rangita Pritish Nandy is an Indian film and web-series producer known for her work in contemporary Hindi cinema and digital content.
- 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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea8779c081908171c58d345d54ae |
completed | April 23, 2026, 9:46 a.m. |
Created at: April 16, 2026, 6:25 p.m.