Triple
T8559072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vikram (2022 film) |
E202645
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Lokesh Kanagaraj |
E202632
|
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: Lokesh Kanagaraj | Statement: [Vikram (2022 film), writer, Lokesh Kanagaraj]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lokesh Kanagaraj Context triple: [Vikram (2022 film), writer, Lokesh Kanagaraj]
-
A.
Lokesh Kanagaraj
chosen
Lokesh Kanagaraj is a prominent Indian film director and screenwriter known for his stylish, high-octane action thrillers in Tamil cinema, including films like "Kaithi," "Master," and "Vikram."
-
B.
Vignesh Shivan
Vignesh Shivan is an Indian film director, producer, lyricist, and actor primarily known for his work in Tamil cinema.
-
C.
Harris Jayaraj
Harris Jayaraj is a prominent Indian film composer best known for his melodious and innovative soundtracks in Tamil cinema.
-
D.
Devi Sri Prasad
Devi Sri Prasad is a prominent Indian film composer and music director best known for his energetic and chart-topping soundtracks in Telugu and other South Indian cinema.
-
E.
Dil Raju
Dil Raju is a prominent Indian film producer and distributor known for backing numerous successful and influential Telugu-language movies.
- 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_69ca8326e6c881908ff720d6abaebdc5 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe9485dd88190bc2cf2adf39d48ee |
completed | March 31, 2026, 3:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf280edb288190a7db5486cc426253 |
completed | April 3, 2026, 2:38 a.m. |
Created at: March 30, 2026, 6:20 p.m.