Triple

T20498256
Position Surface form Disambiguated ID Type / Status
Subject Sylhet Agricultural University E503228 entity
Predicate abbreviation P43 FINISHED
Object SAU
SAU is a public agricultural university located in Sylhet, Bangladesh, specializing in agricultural, veterinary, and related life science education and research.
E1434119 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: SAU | Statement: [Sylhet Agricultural University, abbreviation, SAU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SAU
Context triple: [Sylhet Agricultural University, abbreviation, SAU]
  • A. SAU
    SAU is the three-letter ISO 3166-1 alpha-3 country code assigned to Saudi Arabia.
  • B. SAU
    SAU is an international university established by the South Asian Association for Regional Cooperation (SAARC) in New Delhi, India, focusing on postgraduate and doctoral education and research for students from South Asian countries.
  • C. SAAU
    SAAU is the abbreviated name for the State Aviation Administration of Ukraine, the national authority responsible for regulating and overseeing civil aviation in Ukraine.
  • D. SAAR
    SAAR is the ICAO airport code for Rosario – Islas Malvinas International Airport in Rosario, Argentina.
  • E. SAV
    SAV is the National Rail station code for Stratford-upon-Avon railway station in Warwickshire, England.
  • 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: SAU
Triple: [Sylhet Agricultural University, abbreviation, SAU]
Generated description
SAU is a public agricultural university located in Sylhet, Bangladesh, specializing in agricultural, veterinary, and related life science education and research.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: SAU
Target entity description: SAU is a public agricultural university located in Sylhet, Bangladesh, specializing in agricultural, veterinary, and related life science education and research.
  • A. SAU
    SAU is the three-letter ISO 3166-1 alpha-3 country code assigned to Saudi Arabia.
  • B. SAU
    SAU is an international university established by the South Asian Association for Regional Cooperation (SAARC) in New Delhi, India, focusing on postgraduate and doctoral education and research for students from South Asian countries.
  • C. SAAU
    SAAU is the abbreviated name for the State Aviation Administration of Ukraine, the national authority responsible for regulating and overseeing civil aviation in Ukraine.
  • D. SAAR
    SAAR is the ICAO airport code for Rosario – Islas Malvinas International Airport in Rosario, Argentina.
  • E. SAV
    SAV is the National Rail station code for Stratford-upon-Avon railway station in Warwickshire, England.
  • 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_69e0b4b1e52c8190894281cf7e3283ab completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e69cbff210819089900e9a35911f48 completed April 20, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0893bd1c508190bbba38fb36650723 completed May 16, 2026, 3:56 p.m.
NEDg Description generation batch_6a0894634f748190ae0a3be77125bf03 completed May 16, 2026, 3:59 p.m.
NED2 Entity disambiguation (via description) batch_6a08958072d08190a0e4ba12c7e550ea completed May 16, 2026, 4:04 p.m.
Created at: April 16, 2026, 11:35 a.m.