Triple
T10212813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allah Rakha Rahman |
E242372
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | A. S. Dileep Kumar |
E248877
|
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: A. S. Dileep Kumar | Statement: [Allah Rakha Rahman, birthName, A. S. Dileep Kumar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: A. S. Dileep Kumar Context triple: [Allah Rakha Rahman, birthName, A. S. Dileep Kumar]
-
A.
A. S. Dileep Kumar
chosen
A. S. Dileep Kumar is the birth name of A. R. Rahman, the acclaimed Indian composer, singer, and music producer renowned for his work in film and world music.
-
B.
K. Dinesh
K. Dinesh is an Indian entrepreneur and co-founder of the global IT services and consulting company Infosys.
-
C.
Kishore Sahu
Kishore Sahu was a prominent Indian film director, actor, and producer known for his influential work during the Golden Age of Hindi cinema.
-
D.
M. Sasikumar
M. Sasikumar is an Indian filmmaker and actor best known for his critically acclaimed Tamil film "Subramaniapuram," which he directed and starred in.
-
E.
Dileep Rao
Dileep Rao is an American actor known for his supporting roles in major films such as Avatar, Drag Me to Hell, and Inception.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa23bce881909b5deac612ec22cb |
completed | April 6, 2026, 12:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d652e25be88190a6f1763e9e86666a |
completed | April 8, 2026, 1:06 p.m. |
Created at: April 6, 2026, 11:03 a.m.