Triple
T22094670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chachi 420 |
E545993
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object | V. T. Vijayan |
—
|
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: V. T. Vijayan | Statement: [Chachi 420, editor, V. T. Vijayan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: V. T. Vijayan Context triple: [Chachi 420, editor, V. T. Vijayan]
-
A.
V. T. Vijayan
chosen
V. T. Vijayan is an Indian film editor best known for his acclaimed work in Tamil cinema, including the classic crime drama "Nayakan."
-
B.
Rajam Balachander
Rajam Balachander was the wife of renowned Indian filmmaker K. Balachander and was known for her supportive role in his personal and professional life.
-
C.
G. Aravindan
G. Aravindan was a pioneering Indian filmmaker and cartoonist renowned for his innovative, art-house Malayalam films that profoundly influenced parallel cinema.
-
D.
R. Sasikumar
R. Sasikumar is a former Singaporean footballer and sports entrepreneur known for his contributions to Singapore football both on and off the field.
-
E.
Mala Aravindan
Mala Aravindan was a popular Indian film and stage actor best known for his comic and character roles in Malayalam 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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128e82c1481908701f255b834f192 |
completed | April 28, 2026, 9:38 p.m. |
Created at: April 16, 2026, 8:29 p.m.