Triple
T4951564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shyam Benegal |
E111179
|
entity |
| Predicate | directed |
P7373
|
FINISHED |
| Object | Ankur |
E481982
|
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: Ankur | Statement: [Shyam Benegal, directed, Ankur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ankur Context triple: [Shyam Benegal, directed, Ankur]
-
A.
Ankur
chosen
Ankur is a landmark 1974 Indian Hindi-language film directed by Shyam Benegal that helped launch the parallel cinema movement in India.
-
B.
Anish
Anish is a given name most notably associated with Anish Kapoor, the British-Indian sculptor renowned for his large-scale, often reflective and abstract public artworks.
-
C.
Vivek
Vivek is a common Indian male given name, notably borne by entrepreneur and NBA team owner Vivek Ranadivé.
-
D.
Nishant
Nishant is a critically acclaimed 1975 Indian parallel cinema film directed by Shyam Benegal that explores themes of feudal oppression and social injustice in rural India.
-
E.
Ankit Bhati
Ankit Bhati is an Indian entrepreneur best known as the co-founder and former Chief Technology Officer of the ride-hailing company Ola.
- 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_69bd4418390c8190b7e9766a2512ce55 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd71b561ec81908083225269222e96 |
completed | March 20, 2026, 4:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be92420a5c8190bea911aaf5d6d29b |
completed | March 21, 2026, 12:42 p.m. |
Created at: March 20, 2026, 1:31 p.m.