Triple

T20351415
Position Surface form Disambiguated ID Type / Status
Subject Khandhar E496018 entity
Predicate hasCharacter P2308 FINISHED
Object Prakash
Prakash is a character from the 1984 Hindi film "Khandhar," a critically acclaimed drama directed by Mrinal Sen.
E1425071 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: Prakash | Statement: [Khandhar, hasCharacter, Prakash]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Prakash
Context triple: [Khandhar, hasCharacter, Prakash]
  • A. Pravin
    Pravin is a common Indian given name, notably borne by South African politician and former finance minister Pravin Gordhan.
  • B. Manohar
    Manohar is an Indian given name commonly used for men, often associated with individuals in politics, arts, and public life.
  • C. Behari
    Behari is a fictional character, likely from South Asian literature or drama, connected to the character Ashalata in a significant narrative relationship.
  • D. Bhimsagar
    Bhimsagar is a notable historical site in Rajasthan, India, recognized for its heritage significance within the Jhalawar region.
  • E. Pradip
    Pradip is a masculine given name commonly used in India and among people of Indian origin.
  • 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: Prakash
Triple: [Khandhar, hasCharacter, Prakash]
Generated description
Prakash is a character from the 1984 Hindi film "Khandhar," a critically acclaimed drama directed by Mrinal Sen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Prakash
Target entity description: Prakash is a character from the 1984 Hindi film "Khandhar," a critically acclaimed drama directed by Mrinal Sen.
  • A. Pravin
    Pravin is a common Indian given name, notably borne by South African politician and former finance minister Pravin Gordhan.
  • B. Manohar
    Manohar is an Indian given name commonly used for men, often associated with individuals in politics, arts, and public life.
  • C. Behari
    Behari is a fictional character, likely from South Asian literature or drama, connected to the character Ashalata in a significant narrative relationship.
  • D. Bhimsagar
    Bhimsagar is a notable historical site in Rajasthan, India, recognized for its heritage significance within the Jhalawar region.
  • E. Pradip
    Pradip is a masculine given name commonly used in India and among people of Indian origin.
  • 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_69e0b4a3320881909495ae8bc30bc2dc completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6784f8ff48190a070888786f6a989 completed April 20, 2026, 7:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a086967aef88190b138be722f410e82 completed May 16, 2026, 12:56 p.m.
NEDg Description generation batch_6a0869f7b4208190858fdeae882e008d completed May 16, 2026, 12:58 p.m.
NED2 Entity disambiguation (via description) batch_6a086a893f1c81909bc40e3c4db0e147 completed May 16, 2026, 1 p.m.
Created at: April 16, 2026, 11:24 a.m.