Triple

T3059451
Position Surface form Disambiguated ID Type / Status
Subject Province 5 E60560 entity
Predicate hasMajorCity P316 FINISHED
Object Tansen
Tansen is a historic hill town in western Nepal known for its Newari architecture, panoramic Himalayan views, and cultural significance.
 E321962 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: Tansen | Statement: [Province 5, hasMajorCity, Tansen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tansen
Context triple: [Province 5, hasMajorCity, Tansen]
  • A. Laxmibai
    Laxmibai was the wife of the renowned Kannada poet and Jnanpith awardee D. R. Bendre.
  • B. Lal Chand Ustad
    Lal Chand Ustad was an Indian architect best known for designing Jaipur’s iconic Hawa Mahal, a landmark of Rajput and Mughal architectural fusion.
  • C. Jaya Bhaduri
    Jaya Bhaduri, better known as Jaya Bachchan, is a celebrated Indian actress and politician renowned for her powerful, naturalistic performances in Hindi and Bengali cinema since the 1970s.
  • D. Tyagaraja
    Tyagaraja was a revered 18th–19th century Carnatic composer-saint whose devotional kritis, especially in praise of Lord Rama, are central to South Indian classical music.
  • E. Natarajan Shankar
    Natarajan Shankar is a computer scientist known for his contributions to automated reasoning and formal methods, particularly in theorem proving and verification.
  • 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: Tansen
Triple: [Province 5, hasMajorCity, Tansen]
Generated description
Tansen is a historic hill town in western Nepal known for its Newari architecture, panoramic Himalayan views, and cultural significance.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tansen
Target entity description: Tansen is a historic hill town in western Nepal known for its Newari architecture, panoramic Himalayan views, and cultural significance.
  • A. Laxmibai
    Laxmibai was the wife of the renowned Kannada poet and Jnanpith awardee D. R. Bendre.
  • B. Lal Chand Ustad
    Lal Chand Ustad was an Indian architect best known for designing Jaipur’s iconic Hawa Mahal, a landmark of Rajput and Mughal architectural fusion.
  • C. Jaya Bhaduri
    Jaya Bhaduri, better known as Jaya Bachchan, is a celebrated Indian actress and politician renowned for her powerful, naturalistic performances in Hindi and Bengali cinema since the 1970s.
  • D. Tyagaraja
    Tyagaraja was a revered 18th–19th century Carnatic composer-saint whose devotional kritis, especially in praise of Lord Rama, are central to South Indian classical music.
  • E. Natarajan Shankar
    Natarajan Shankar is a computer scientist known for his contributions to automated reasoning and formal methods, particularly in theorem proving and verification.
  • 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_69ad8578137c81908259dcb27c7d6d7c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ad9e9cf9188190b43f50edc009030d completed March 8, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1ef0b989c819094daaf222bf01d02 completed March 11, 2026, 10:39 p.m.
NEDg Description generation batch_69b1efdd73188190b7a47fc2a1d627d1 completed March 11, 2026, 10:42 p.m.
NED2 Entity disambiguation (via description) batch_69b1f062abf48190ab891463c5b33622 completed March 11, 2026, 10:44 p.m.
Created at: March 8, 2026, 3:02 p.m.