Triple
T8558316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nayanthara |
E202631
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Billa |
E743500
|
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: Billa | Statement: [Nayanthara, notableWork, Billa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Billa Context triple: [Nayanthara, notableWork, Billa]
-
A.
Billa
Billa is a 2009 Telugu-language action thriller film starring Prabhas, known for its stylish remake of the 1980s Chiranjeevi classic of the same name.
-
B.
Billa
chosen
Billa is a 1980 Indian Tamil-language action film starring Rajinikanth, known for its stylish portrayal of an underworld don and its status as a landmark gangster movie in Tamil cinema.
-
C.
Badal
Badal is a Barcelona Metro station that serves the area near Camp Nou stadium in Barcelona, Spain.
-
D.
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.
-
E.
Kaalpurush
Kaalpurush is an acclaimed Bengali film by director Buddhadeb Dasgupta that explores memory, time, and human relationships through a poetic, surreal narrative.
- 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_69cea871dd3081908e24c4d1c60a8381 |
completed | April 2, 2026, 5:33 p.m. |
Created at: March 30, 2026, 6:20 p.m.