Triple
T1436833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Satyajit Ray |
E30576
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Satyajit |
E30576
|
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: Satyajit | Statement: [Satyajit Ray, givenName, Satyajit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Satyajit Context triple: [Satyajit Ray, givenName, Satyajit]
-
A.
Narayan Apte
Narayan Apte was an Indian nationalist and co-conspirator in the assassination of Mahatma Gandhi, executed for his role in the plot.
-
B.
Satyajit Ray
chosen
Satyajit Ray was an acclaimed Indian filmmaker, writer, and artist from Bengal, renowned worldwide for his pioneering contributions to cinema and his profound influence on modern Indian culture.
-
C.
Satyajit Sen
Satyajit Sen is an individual notable enough to be recognized as a distinguished bearer of the surname Sen.
-
D.
Dilip Hiro
Dilip Hiro is a British-based Indian author, journalist, and commentator known for his extensive writings on Middle Eastern politics, South Asia, and global geopolitics.
-
E.
Om Puri
Om Puri was a renowned Indian actor celebrated for his powerful performances in both parallel and mainstream cinema, as well as notable roles in international films.
- 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_69a498fc69ec8190b61722bd4b67c4d2 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c50418d08190ace2cab98af87f29 |
completed | March 1, 2026, 11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad1c9999b0819086573fb974952f63 |
completed | March 8, 2026, 6:52 a.m. |
Created at: March 1, 2026, 8 p.m.