Triple

T2221707
Position Surface form Disambiguated ID Type / Status
Subject S. L. Bhyrappa E48154 entity
Predicate notableWork P4 FINISHED
Object Tantu
Tantu is a Kannada novel by acclaimed Indian writer S. L. Bhyrappa, known for its exploration of complex social and philosophical themes.
 E252077 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: Tantu | Statement: [S. L. Bhyrappa, notableWork, Tantu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tantu
Context triple: [S. L. Bhyrappa, notableWork, Tantu]
  • A. Kassala
    Kassala is a city in eastern Sudan near the Eritrean border, known as a regional trade center and for its striking granite hills and cultural diversity.
  • B. Wazzu
    Wazzu is a popular nickname for Washington State University, a public research university located in Pullman, Washington.
  • C. Tanta
    Tanta is a major city in northern Egypt that serves as an important commercial and transportation hub in the Nile Delta.
  • D. Dongola
    Dongola is a historic town in northern Sudan that served as a major political and cultural center of medieval Nubian kingdoms along the Nile.
  • E. Ras Lanuf
    Ras Lanuf is a major oil port and industrial town on Libya’s Mediterranean coast, known for its large refinery and strategic role in the country’s petroleum exports.
  • 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: Tantu
Triple: [S. L. Bhyrappa, notableWork, Tantu]
Generated description
Tantu is a Kannada novel by acclaimed Indian writer S. L. Bhyrappa, known for its exploration of complex social and philosophical themes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tantu
Target entity description: Tantu is a Kannada novel by acclaimed Indian writer S. L. Bhyrappa, known for its exploration of complex social and philosophical themes.
  • A. Kassala
    Kassala is a city in eastern Sudan near the Eritrean border, known as a regional trade center and for its striking granite hills and cultural diversity.
  • B. Wazzu
    Wazzu is a popular nickname for Washington State University, a public research university located in Pullman, Washington.
  • C. Tanta
    Tanta is a major city in northern Egypt that serves as an important commercial and transportation hub in the Nile Delta.
  • D. Dongola
    Dongola is a historic town in northern Sudan that served as a major political and cultural center of medieval Nubian kingdoms along the Nile.
  • E. Ras Lanuf
    Ras Lanuf is a major oil port and industrial town on Libya’s Mediterranean coast, known for its large refinery and strategic role in the country’s petroleum exports.
  • 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_69a88aa1ee708190862c8c378c41e9eb completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc03bfdd48190bfb96ec3e41c22dc completed March 7, 2026, 6:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae7efdb7a08190b74e841279b59971 completed March 9, 2026, 8:04 a.m.
NEDg Description generation batch_69ae7f90d3a88190bf61c6f063b67c06 completed March 9, 2026, 8:06 a.m.
NED2 Entity disambiguation (via description) batch_69ae800868948190a5504969c4cabb7d completed March 9, 2026, 8:08 a.m.
Created at: March 4, 2026, 7:47 p.m.