Triple
T19391266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhumika |
E485072
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Anant Nag |
—
|
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: Anant Nag | Statement: [Bhumika, starring, Anant Nag]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anant Nag Context triple: [Bhumika, starring, Anant Nag]
-
A.
Anant Nag
chosen
Anant Nag is a renowned Indian actor known primarily for his work in Kannada cinema, acclaimed for his versatile performances in both parallel and mainstream films.
-
B.
Madan Babu
Madan Babu is a computational biologist known for his influential work on gene regulation, protein networks, and systems biology.
-
C.
Shashi Kaushik
Shashi Kaushik is known as the wife of the late Indian actor, director, and producer Satish Kaushik.
-
D.
Anup Kumar
Anup Kumar is an Indian kabaddi player renowned for his leadership of the national team and his success in the Pro Kabaddi League.
-
E.
Prakash Raj
Prakash Raj is an acclaimed Indian actor, filmmaker, and producer known for his versatile performances across multiple South Indian film industries and Hindi cinema.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61b44b70c81908e2f0deeabe4360f |
completed | April 20, 2026, 12:25 p.m. |
Created at: April 10, 2026, 1:36 p.m.