Triple
T7772187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tapan Sinha |
E179098
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Atanka
Atanka is an Indian Bengali-language film directed by Tapan Sinha, known for its tense portrayal of fear and moral conflict in a rural setting.
|
E687318
|
NE FINISHED |
How this triple was built (4 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: Atanka | Statement: [Tapan Sinha, notableWork, Atanka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Atanka Context triple: [Tapan Sinha, notableWork, Atanka]
-
A.
Atacazo
Atacazo is a stratovolcano in the Andes of central Ecuador, located southwest of Quito and known for its prominent peak within the Cordillera Occidental range.
-
B.
Groza
Groza is a surname most notably associated with Lou Groza, a Hall of Fame American football placekicker and offensive tackle for the Cleveland Browns.
-
C.
Talifuguen
Talifuguen is a dialect of the Isnag language spoken by indigenous communities in the northern Philippines.
-
D.
Bomba
Bomba is a traditional Afro-Puerto Rican musical and dance genre characterized by call-and-response singing, barrel drums, and improvisational interaction between dancers and drummers.
-
E.
Bucksturm
Bucksturm is a historic medieval tower in Osnabrück, Germany, known for its former use as a city fortification and prison.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Atanka Triple: [Tapan Sinha, notableWork, Atanka]
Generated description
Atanka is an Indian Bengali-language film directed by Tapan Sinha, known for its tense portrayal of fear and moral conflict in a rural setting.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Atanka Target entity description: Atanka is an Indian Bengali-language film directed by Tapan Sinha, known for its tense portrayal of fear and moral conflict in a rural setting.
-
A.
Atacazo
Atacazo is a stratovolcano in the Andes of central Ecuador, located southwest of Quito and known for its prominent peak within the Cordillera Occidental range.
-
B.
Groza
Groza is a surname most notably associated with Lou Groza, a Hall of Fame American football placekicker and offensive tackle for the Cleveland Browns.
-
C.
Talifuguen
Talifuguen is a dialect of the Isnag language spoken by indigenous communities in the northern Philippines.
-
D.
Bomba
Bomba is a traditional Afro-Puerto Rican musical and dance genre characterized by call-and-response singing, barrel drums, and improvisational interaction between dancers and drummers.
-
E.
Bucksturm
Bucksturm is a historic medieval tower in Osnabrück, Germany, known for its former use as a city fortification and prison.
- F. None of above. chosen
Provenance (5 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_69c69f30602c819082ab52cd4af5c592 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c7046048688190a6cbc64e82b58eca |
completed | March 27, 2026, 10:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8c7ee407881908e591d216c504b24 |
completed | March 29, 2026, 6:34 a.m. |
| NEDg | Description generation | batch_69c8c8b75b848190a67de2040d563f86 |
completed | March 29, 2026, 6:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8c941814081909d299df5cd714c71 |
completed | March 29, 2026, 6:40 a.m. |
Created at: March 27, 2026, 4:11 p.m.