Triple
T14847312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victor Banerjee |
E349131
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Bhootnath
Bhootnath is an Indian film best known for featuring Victor Banerjee in a significant role.
|
E1124498
|
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: Bhootnath | Statement: [Victor Banerjee, notableWork, Bhootnath]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bhootnath Context triple: [Victor Banerjee, notableWork, Bhootnath]
-
A.
Kaalpurush
Kaalpurush is an acclaimed Bengali film by director Buddhadeb Dasgupta that explores memory, time, and human relationships through a poetic, surreal narrative.
-
B.
Bughotu
Bughotu is an Austronesian language spoken by communities on Santa Isabel Island in the Solomon Islands.
-
C.
Badal
Badal is a Barcelona Metro station that serves the area near Camp Nou stadium in Barcelona, Spain.
-
D.
Phillauri
Phillauri is a 2017 Indian romantic comedy-drama film that blends elements of fantasy and reincarnation, featuring a ghost bride entangled in a modern-day Punjabi wedding.
-
E.
Billa
Billa is a 2009 Telugu-language action thriller film starring Prabhas, known for its stylish remake of the 1980s Chiranjeevi classic of the same name.
- 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: Bhootnath Triple: [Victor Banerjee, notableWork, Bhootnath]
Generated description
Bhootnath is an Indian film best known for featuring Victor Banerjee in a significant role.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bhootnath Target entity description: Bhootnath is an Indian film best known for featuring Victor Banerjee in a significant role.
-
A.
Kaalpurush
Kaalpurush is an acclaimed Bengali film by director Buddhadeb Dasgupta that explores memory, time, and human relationships through a poetic, surreal narrative.
-
B.
Bughotu
Bughotu is an Austronesian language spoken by communities on Santa Isabel Island in the Solomon Islands.
-
C.
Badal
Badal is a Barcelona Metro station that serves the area near Camp Nou stadium in Barcelona, Spain.
-
D.
Phillauri
Phillauri is a 2017 Indian romantic comedy-drama film that blends elements of fantasy and reincarnation, featuring a ghost bride entangled in a modern-day Punjabi wedding.
-
E.
Billa
Billa is a 2009 Telugu-language action thriller film starring Prabhas, known for its stylish remake of the 1980s Chiranjeevi classic of the same name.
- 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_69d822ec69008190a9232caa68836872 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded29236dc8190b7d3a37d09f9fb21 |
completed | April 14, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6502d3f081909ff6fa8722769e2e |
completed | May 8, 2026, 10:34 p.m. |
| NEDg | Description generation | batch_69fe662fa374819083367ba7f9da2272 |
completed | May 8, 2026, 10:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe67664044819084196e3e6e365415 |
completed | May 8, 2026, 10:44 p.m. |
Created at: April 10, 2026, 1:53 a.m.