Triple
T8558919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roja |
E202642
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | Roja |
E202642
|
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: Roja | Statement: [Roja, title, Roja]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roja Context triple: [Roja, title, Roja]
-
A.
Roja
chosen
Roja is a critically acclaimed 1992 Indian Tamil-language political thriller film directed by Mani Ratnam, noted for its powerful storytelling and A. R. Rahman's debut film score.
-
B.
Meenas
The Meenas are an indigenous tribal community of northern India, historically associated with agrarian livelihoods, local chieftaincies, and a distinct cultural and religious heritage.
-
C.
Yannai
Yannai is another name for Alexander Jannaeus, a Hasmonean king of Judea and high priest who ruled in the early 1st century BCE.
-
D.
Dhool
Dhool is a popular 2003 Tamil action-comedy film starring Vikram, known for its mass appeal, energetic performances, and hit soundtrack.
-
E.
Rangbaaz
Rangbaaz is a Bangladeshi film that helped establish actor Razzak as a major star in the country’s cinema.
- 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_69ce894d82588190b558d5b2dc65eafe |
completed | April 2, 2026, 3:20 p.m. |
Created at: March 30, 2026, 6:20 p.m.