Triple

T8527975
Position Surface form Disambiguated ID Type / Status
Subject Prosenjit Chatterjee E201866 entity
Predicate alsoKnownAs P39 FINISHED
Object Prosenjit
Prosenjit is a prominent Indian film actor and producer, best known for his leading roles in Bengali cinema since the 1980s.
 E742123 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: Prosenjit | Statement: [Prosenjit Chatterjee, alsoKnownAs, Prosenjit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Prosenjit
Context triple: [Prosenjit Chatterjee, alsoKnownAs, Prosenjit]
  • A. Prasun
    Prasun is an indigenous ethnic group from the Nuristan region of Afghanistan, known for its distinct culture and language within the Indo-Iranian family.
  • B. Nabaneeta
    Nabaneeta is a feminine given name most notably borne by the acclaimed Indian Bengali writer and academic Nabaneeta Dev Sen.
  • C. Swarup
    Swarup is an Indian given name commonly used for males, derived from Sanskrit and generally meaning "form" or "true nature."
  • D. Savyasachi
    Savyasachi is a celebrated epithet of the Mahabharata hero Arjuna, highlighting his legendary ambidextrous skill in archery and combat.
  • E. Surama Ghatak
    Surama Ghatak was the wife of renowned Indian filmmaker Ritwik Ghatak and a figure associated with his personal and artistic life.
  • 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: Prosenjit
Triple: [Prosenjit Chatterjee, alsoKnownAs, Prosenjit]
Generated description
Prosenjit is a prominent Indian film actor and producer, best known for his leading roles in Bengali cinema since the 1980s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Prosenjit
Target entity description: Prosenjit is a prominent Indian film actor and producer, best known for his leading roles in Bengali cinema since the 1980s.
  • A. Prasun
    Prasun is an indigenous ethnic group from the Nuristan region of Afghanistan, known for its distinct culture and language within the Indo-Iranian family.
  • B. Nabaneeta
    Nabaneeta is a feminine given name most notably borne by the acclaimed Indian Bengali writer and academic Nabaneeta Dev Sen.
  • C. Swarup
    Swarup is an Indian given name commonly used for males, derived from Sanskrit and generally meaning "form" or "true nature."
  • D. Savyasachi
    Savyasachi is a celebrated epithet of the Mahabharata hero Arjuna, highlighting his legendary ambidextrous skill in archery and combat.
  • E. Surama Ghatak
    Surama Ghatak was the wife of renowned Indian filmmaker Ritwik Ghatak and a figure associated with his personal and artistic life.
  • 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_69ca83228b24819085d22e7dc99f5d94 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe672e0588190a84328e1bf974f08 completed March 31, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6d54ef908190970a1010c8018abd completed April 2, 2026, 1:21 p.m.
NEDg Description generation batch_69ce71cd3320819090f2e09f51493f9a completed April 2, 2026, 1:40 p.m.
NED2 Entity disambiguation (via description) batch_69ce725a4cf081909cd470fd4d7452ca completed April 2, 2026, 1:42 p.m.
Created at: March 30, 2026, 6:17 p.m.