Triple

T16183439
Position Surface form Disambiguated ID Type / Status
Subject Raja Hindustani E392740 entity
Predicate editedBy P1954 FINISHED
Object Bharat Singh
Bharat Singh is a film editor known for his work on the popular Hindi movie "Raja Hindustani."
E1205614 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: Bharat Singh | Statement: [Raja Hindustani, editedBy, Bharat Singh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bharat Singh
Context triple: [Raja Hindustani, editedBy, Bharat Singh]
  • A. Roshan Singh
    Roshan Singh was an Indian revolutionary and freedom fighter associated with the Hindustan Republican Association who participated in anti-colonial activities against British rule in the early 20th century.
  • B. Jagdanand Singh
    Jagdanand Singh is an Indian politician and senior leader of the Rashtriya Janata Dal, known for his long-standing role in Bihar state politics.
  • C. Tej Singh
    Tej Singh was a prominent Sikh military leader and general who played a key role in the Anglo-Sikh Wars against the British in the mid-19th century.
  • D. Sher Singh
    Sher Singh was a 19th-century Maharaja of the Sikh Empire who briefly ruled Punjab during the turbulent period following Maharaja Ranjit Singh’s death.
  • E. Beant Singh
    Beant Singh was one of the Sikh bodyguards who assassinated Indian Prime Minister Indira Gandhi in 1984.
  • 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: Bharat Singh
Triple: [Raja Hindustani, editedBy, Bharat Singh]
Generated description
Bharat Singh is a film editor known for his work on the popular Hindi movie "Raja Hindustani."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Bharat Singh
Target entity description: Bharat Singh is a film editor known for his work on the popular Hindi movie "Raja Hindustani."
  • A. Roshan Singh
    Roshan Singh was an Indian revolutionary and freedom fighter associated with the Hindustan Republican Association who participated in anti-colonial activities against British rule in the early 20th century.
  • B. Jagdanand Singh
    Jagdanand Singh is an Indian politician and senior leader of the Rashtriya Janata Dal, known for his long-standing role in Bihar state politics.
  • C. Tej Singh
    Tej Singh was a prominent Sikh military leader and general who played a key role in the Anglo-Sikh Wars against the British in the mid-19th century.
  • D. Sher Singh
    Sher Singh was a 19th-century Maharaja of the Sikh Empire who briefly ruled Punjab during the turbulent period following Maharaja Ranjit Singh’s death.
  • E. Beant Singh
    Beant Singh was one of the Sikh bodyguards who assassinated Indian Prime Minister Indira Gandhi in 1984.
  • 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e2205ef39081908da383abdebc2ccc completed April 17, 2026, 11:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a001f860ecc8190be904fa793968d89 completed May 10, 2026, 6:02 a.m.
NEDg Description generation batch_6a00211bb2bc8190bc32492fd6de3bc3 completed May 10, 2026, 6:09 a.m.
NED2 Entity disambiguation (via description) batch_6a00221262288190b154d2e2c318d162 completed May 10, 2026, 6:13 a.m.
Created at: April 10, 2026, 5:02 a.m.