Triple

T10521898
Position Surface form Disambiguated ID Type / Status
Subject Graz University of Technology E248192 entity
Predicate abbreviation P43 FINISHED
Object TUG
TUG is the commonly used abbreviation for Graz University of Technology, a major Austrian university specializing in engineering and technical sciences.
 E869218 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: TUG | Statement: [Graz University of Technology, abbreviation, TUG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TUG
Context triple: [Graz University of Technology, abbreviation, TUG]
  • A. TOG
    TOG is the commonly used abbreviation for The Open Group, an international consortium that develops open, vendor-neutral technology standards and certifications.
  • B. TWG
    TWG is the commonly used abbreviation for The World Games, an international multi-sport event featuring disciplines not contested in the Olympic Games.
  • C. Tugen
    Tugen is a Southern Nilotic language spoken primarily by the Tugen people of Kenya’s Rift Valley region.
  • D. TGO
    TGO is the three-letter ISO 3166-1 alpha-3 country code assigned to the West African nation of Togo.
  • E. Tu
    Tu Youyou is a Chinese pharmaceutical chemist and Nobel laureate renowned for discovering the antimalarial drug artemisinin.
  • 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: TUG
Triple: [Graz University of Technology, abbreviation, TUG]
Generated description
TUG is the commonly used abbreviation for Graz University of Technology, a major Austrian university specializing in engineering and technical sciences.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TUG
Target entity description: TUG is the commonly used abbreviation for Graz University of Technology, a major Austrian university specializing in engineering and technical sciences.
  • A. TOG
    TOG is the commonly used abbreviation for The Open Group, an international consortium that develops open, vendor-neutral technology standards and certifications.
  • B. TWG
    TWG is the commonly used abbreviation for The World Games, an international multi-sport event featuring disciplines not contested in the Olympic Games.
  • C. Tugen
    Tugen is a Southern Nilotic language spoken primarily by the Tugen people of Kenya’s Rift Valley region.
  • D. TGO
    TGO is the three-letter ISO 3166-1 alpha-3 country code assigned to the West African nation of Togo.
  • E. Tu
    The Tu are a Mongolic-speaking ethnic minority in northwestern China, known for their Tibetan Buddhist traditions and distinctive agrarian culture in Qinghai and Gansu provinces.
  • 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_69d381c5c7448190bec34bee7ec72bac completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509e0907481908807dd99980cba1f completed April 7, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d90e119fe4819085e5c1c6e71e6260 completed April 10, 2026, 2:49 p.m.
NEDg Description generation batch_69d9107e8b94819086ebba1675a0db54 completed April 10, 2026, 3 p.m.
NED2 Entity disambiguation (via description) batch_69d911a16b1481909197b00c30de48c4 completed April 10, 2026, 3:05 p.m.
Created at: April 6, 2026, 12:29 p.m.