Triple

T377353
Position Surface form Disambiguated ID Type / Status
Subject Kannada E8600 entity
Predicate hasNotablePoet P4290 FINISHED
Object Ponna
Ponna was a prominent 10th-century Kannada poet of the Rashtrakuta court, renowned for his Jain devotional and classical literary works.
 E47757 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: Ponna | Statement: [Kannada, hasNotablePoet, Ponna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ponna
Context triple: [Kannada, hasNotablePoet, Ponna]
  • A. Yerrapragada
    Yerrapragada was a prominent medieval Telugu poet and scholar, renowned for his contributions to classical Telugu literature and refinement of earlier works.
  • B. Ahirani
    Ahirani is an Indo-Aryan dialect spoken primarily in the Khandesh region of Maharashtra, India, closely related to Marathi but with distinct phonological and lexical features.
  • C. Premji
    Premji is an Indian surname most prominently associated with billionaire philanthropist and Wipro chairman Azim Premji.
  • D. Sibi
    Sibi is a historic town and district in the Balochistan region of Pakistan, known for its hot climate and traditional annual cattle and horse fair.
  • E. Kalpeni
    Kalpeni is a coral atoll and inhabited island in India’s Lakshadweep archipelago in the Arabian Sea, known for its lagoon, beaches, and coconut groves.
  • 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: Ponna
Triple: [Kannada, hasNotablePoet, Ponna]
Generated description
Ponna was a prominent 10th-century Kannada poet of the Rashtrakuta court, renowned for his Jain devotional and classical literary works.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ponna
Target entity description: Ponna was a prominent 10th-century Kannada poet of the Rashtrakuta court, renowned for his Jain devotional and classical literary works.
  • A. Yerrapragada
    Yerrapragada was a prominent medieval Telugu poet and scholar, renowned for his contributions to classical Telugu literature and refinement of earlier works.
  • B. Ahirani
    Ahirani is an Indo-Aryan dialect spoken primarily in the Khandesh region of Maharashtra, India, closely related to Marathi but with distinct phonological and lexical features.
  • C. Premji
    Premji is an Indian surname most prominently associated with billionaire philanthropist and Wipro chairman Azim Premji.
  • D. Sibi
    Sibi is a historic town and district in the Balochistan region of Pakistan, known for its hot climate and traditional annual cattle and horse fair.
  • E. Kalpeni
    Kalpeni is a coral atoll and inhabited island in India’s Lakshadweep archipelago in the Arabian Sea, known for its lagoon, beaches, and coconut groves.
  • 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_69a2e7f47dd08190a4e294ccbbe46cd4 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ec1804108190a1e94526b71289ea completed Feb. 28, 2026, 1:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3f4dd9a1c8190a0fc7012a24425c4 completed March 1, 2026, 8:12 a.m.
NEDg Description generation batch_69a3f68ca09c81909c3ce88fe6c591dc completed March 1, 2026, 8:19 a.m.
NED2 Entity disambiguation (via description) batch_69a3f6fd5fa48190b79f9eaea79c4dec completed March 1, 2026, 8:21 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.