Triple
T21265554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anant Nag |
E524114
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | K.G.F: Chapter 2 |
—
|
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: K.G.F: Chapter 2 | Statement: [Anant Nag, notableWork, K.G.F: Chapter 2]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: K.G.F: Chapter 2 Context triple: [Anant Nag, notableWork, K.G.F: Chapter 2]
-
A.
K.G.F: Chapter 2
chosen
K.G.F: Chapter 2 is a 2022 Indian Kannada-language action film and the sequel to K.G.F: Chapter 1, known for its high-octane storytelling, stylized violence, and massive box-office success.
-
B.
K.G.F: Chapter 1
K.G.F: Chapter 1 is a 2018 Indian Kannada-language period action film that follows the rise of a ruthless gangster in the Kolar Gold Fields and became a major pan-Indian blockbuster.
-
C.
KGF
KGF is the IATA airport code for Sary-Arka Airport, which serves the city of Karaganda in Kazakhstan.
-
D.
Kabali
Kabali is a 2016 Indian Tamil-language action drama film starring Rajinikanth as an aging gangster seeking revenge and redemption.
-
E.
Gaga Bhatt
Gaga Bhatt was a prominent 17th-century Hindu scholar and priest from Varanasi, best known for officiating the royal coronation of the Maratha ruler Shivaji.
- 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_69e0b5156d7881909bd4f83676590715 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e735ebe09081909f74301e91b4d3d7 |
completed | April 21, 2026, 8:31 a.m. |
Created at: April 16, 2026, 4 p.m.