Triple
T8559106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vikram (2022 film) |
E202645
|
entity |
| Predicate | follows |
P134
|
FINISHED |
| Object | Kaithi (2019 film) |
E746021
|
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 (2019 film) | Statement: [Vikram (2022 film), follows, Kaithi (2019 film)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaithi (2019 film) Context triple: [Vikram (2022 film), follows, Kaithi (2019 film)]
-
A.
Kaithi
Kaithi is a historical Brahmic script from northern India that was used to write several Indo-Aryan languages, including Bhojpuri, Magahi, and Maithili.
-
B.
Kaithi
chosen
Kaithi is a 2019 Tamil-language action thriller film centered on an ex-convict’s overnight mission to save poisoned police officers while evading ruthless criminals.
-
C.
Kabali
Kabali is a 2016 Indian Tamil-language action drama film starring Rajinikanth as an aging gangster seeking revenge and redemption.
-
D.
Kaththi
Kaththi is a 2014 Tamil action-drama film directed by A.R. Murugadoss, starring Vijay in a dual role and focusing on social issues like farmer exploitation and corporate greed.
-
E.
Drishyam
Drishyam is a critically acclaimed Indian thriller film known for its intricate plot, suspenseful storytelling, and strong performances.
- 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_69cecc6a63488190a03d1f5e80ac28b4 |
completed | April 2, 2026, 8:07 p.m. |
Created at: March 30, 2026, 6:20 p.m.