Triple

T14876548
Position Surface form Disambiguated ID Type / Status
Subject Harsha Bhogle E349882 entity
Predicate givenName P17 FINISHED
Object Harsha
Harsha is a prominent Indian cricket commentator and journalist known for his insightful analysis and articulate broadcasting style.
 E1126026 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: Harsha | Statement: [Harsha Bhogle, givenName, Harsha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Harsha
Context triple: [Harsha Bhogle, givenName, Harsha]
  • A. Harsha
    Harsha was a 7th-century Indian emperor who unified much of northern India and became renowned for his patronage of Buddhism, literature, and the arts.
  • B. Haripal
    Haripal is a town in West Bengal, India, known for its railway junction and role as a local commercial and agricultural center within Hooghly district.
  • C. Harish
    Harish is the given name of Harish-Chandra, a prominent Indian-American mathematician and physicist known for his foundational work in representation theory.
  • D. Akrura
    Akrura is a revered figure in Hindu mythology, known as a devout Yadava charioteer and ally of Krishna who played a key role in bringing him to Mathura.
  • E. Sudarshan
    Sudarshan is a common Indian surname found across various regions and communities in India.
  • 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: Harsha
Triple: [Harsha Bhogle, givenName, Harsha]
Generated description
Harsha is a prominent Indian cricket commentator and journalist known for his insightful analysis and articulate broadcasting style.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Harsha
Target entity description: Harsha is a prominent Indian cricket commentator and journalist known for his insightful analysis and articulate broadcasting style.
  • A. Harsha
    Harsha was a 7th-century Indian emperor who unified much of northern India and became renowned for his patronage of Buddhism, literature, and the arts.
  • B. Haripal
    Haripal is a town in West Bengal, India, known for its railway junction and role as a local commercial and agricultural center within Hooghly district.
  • C. Harish
    Harish is the given name of Harish-Chandra, a prominent Indian-American mathematician and physicist known for his foundational work in representation theory.
  • D. Akrura
    Akrura is a revered figure in Hindu mythology, known as a devout Yadava charioteer and ally of Krishna who played a key role in bringing him to Mathura.
  • E. Sudarshan
    Sudarshan is a common Indian surname found across various regions and communities in India.
  • 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5e4e4448190a8796573bc6d1069 completed April 15, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b54ad7c819082575245da07e358 completed May 8, 2026, 11:01 p.m.
NEDg Description generation batch_69fe6be21f148190bec0e5adfcc0a91a completed May 8, 2026, 11:04 p.m.
NED2 Entity disambiguation (via description) batch_69fe6c6ebe4881909334d772e45403f6 completed May 8, 2026, 11:06 p.m.
Created at: April 10, 2026, 1:55 a.m.