Triple
T7816001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rituparno Ghosh |
E181008
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Abohoman
Abohoman is a Bengali film directed by Rituparno Ghosh that explores complex relationships and the blurred boundaries between art and life in the world of cinema.
|
E694841
|
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: Abohoman | Statement: [Rituparno Ghosh, notableWork, Abohoman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abohoman Context triple: [Rituparno Ghosh, notableWork, Abohoman]
-
A.
Itabi
Itabi is a small municipality in the Brazilian state of Sergipe, known for its rural character and location in the semi-arid interior region.
-
B.
Nabaloi
Nabaloi is an Austronesian language spoken by the Ibaloi people of the northern Philippines, particularly in the Benguet region of Luzon.
-
C.
Othomi
Othomi is an alternative name for the Otomi people and their indigenous language of central Mexico.
-
D.
Zogoiby
Zogoiby is the surname of Aurora Zogoiby, a character from Salman Rushdie’s novel "The Moor’s Last Sigh."
-
E.
Kabaena
Kabaena is an island in Indonesia known for its location off the coast of Sulawesi and its mix of coastal and hilly landscapes.
- 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: Abohoman Triple: [Rituparno Ghosh, notableWork, Abohoman]
Generated description
Abohoman is a Bengali film directed by Rituparno Ghosh that explores complex relationships and the blurred boundaries between art and life in the world of cinema.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Abohoman Target entity description: Abohoman is a Bengali film directed by Rituparno Ghosh that explores complex relationships and the blurred boundaries between art and life in the world of cinema.
-
A.
Itabi
Itabi is a small municipality in the Brazilian state of Sergipe, known for its rural character and location in the semi-arid interior region.
-
B.
Nabaloi
Nabaloi is an Austronesian language spoken by the Ibaloi people of the northern Philippines, particularly in the Benguet region of Luzon.
-
C.
Othomi
Othomi is an alternative name for the Otomi people and their indigenous language of central Mexico.
-
D.
Zogoiby
Zogoiby is the surname of Aurora Zogoiby, a character from Salman Rushdie’s novel "The Moor’s Last Sigh."
-
E.
Kabaena
Kabaena is an island in Indonesia known for its location off the coast of Sulawesi and its mix of coastal and hilly landscapes.
- 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_69ca828153f48190bdb27ac46f8e0745 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf96d1f088190a1d005ffb019afe9 |
completed | March 30, 2026, 10:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb1488a2e48190924f44b46f925d87 |
completed | March 31, 2026, 12:25 a.m. |
| NEDg | Description generation | batch_69cb1732bb608190aa776f23f0dc6189 |
completed | March 31, 2026, 12:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cb1a62569c81908709d814954f667e |
completed | March 31, 2026, 12:50 a.m. |
Created at: March 30, 2026, 4:39 p.m.