Triple
T8564878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suriya |
E202778
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Jyothika |
E202780
|
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: Jyothika | Statement: [Suriya, spouse, Jyothika]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jyothika Context triple: [Suriya, spouse, Jyothika]
-
A.
Jyothika
chosen
Jyothika is a prominent Indian film actress best known for her leading roles in Tamil-language movies, where she has earned critical acclaim and several major awards.
-
B.
Ramya Krishnan
Ramya Krishnan is an acclaimed Indian actress known for her powerful and versatile performances across Tamil, Telugu, and other South Indian film industries.
-
C.
Nayanthara
Nayanthara is a leading Indian film actress, often called the "Lady Superstar" of South Indian cinema, known for her versatile performances in Tamil, Telugu, and Malayalam films.
-
D.
Rani Mukerji
Rani Mukerji is an acclaimed Indian film actress known for her versatile performances in numerous successful Hindi movies since the late 1990s.
-
E.
Juhi Chawla
Juhi Chawla is a popular Indian actress and film producer known for her work in Hindi cinema since the late 1980s.
- 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_69ca8327b0a881908606ff860713964d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe9d11274819099cc33a21a993a1f |
completed | March 31, 2026, 3:35 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.