Triple
T21330846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mohan Agashe |
E525893
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Manthan |
—
|
NE NERFINISHED |
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: Manthan | Statement: [Mohan Agashe, notableWork, Manthan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Manthan Context triple: [Mohan Agashe, notableWork, Manthan]
-
A.
Manthan
chosen
Manthan is a landmark 1976 Indian film directed by Shyam Benegal that dramatizes the origins of India’s rural milk cooperative movement, inspired by the White Revolution.
-
B.
Naman
Naman is an endangered Oceanic language spoken by a small community in Vanuatu.
-
C.
Namanve
Namanve is an industrial and commercial area in central Uganda known for hosting the Kampala Industrial and Business Park and various manufacturing facilities.
-
D.
Mandarmani
Mandarmani is a seaside resort village in West Bengal, India, known for its long, drivable beach and growing popularity as a quieter alternative to busier coastal destinations.
-
E.
Manjai Kunda
Manjai Kunda is a residential neighborhood within the urban area of Serekunda in The Gambia.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b51b90788190a4dd823d962626da |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7ab5177dc8190b888351e9a45b45f |
completed | April 21, 2026, 4:52 p.m. |
Created at: April 16, 2026, 4:42 p.m.