Triple
T8558362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lokesh Kanagaraj |
E202632
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Kaithi |
E710287
|
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: Kaithi | Statement: [Lokesh Kanagaraj, notableWork, Kaithi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaithi Context triple: [Lokesh Kanagaraj, notableWork, Kaithi]
-
A.
Kaithi
chosen
Kaithi is a historical Brahmic script from northern India that was used to write several Indo-Aryan languages, including Bhojpuri, Magahi, and Maithili.
-
B.
Kabali
Kabali is a 2016 Indian Tamil-language action drama film starring Rajinikanth as an aging gangster seeking revenge and redemption.
-
C.
Drishyam
Drishyam is a critically acclaimed Indian thriller film known for its intricate plot, suspenseful storytelling, and strong performances.
-
D.
Jawan
Jawan is a 2023 Indian action thriller film starring Shah Rukh Khan, known for its high-octane action, social themes, and massive box-office success.
-
E.
Bheemla Nayak
Bheemla Nayak is a 2022 Telugu-language action drama film, a remake of the Malayalam movie Ayyappanum Koshiyum, known for its intense face-off between a principled cop and an influential ex-army man.
- 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_69ce89455dcc819088bdf5a2f653da17 |
completed | April 2, 2026, 3:20 p.m. |
Created at: March 30, 2026, 6:20 p.m.