Triple

T3002125
Position Surface form Disambiguated ID Type / Status
Subject Vienna University of Technology E81810 entity
Predicate hasAbbreviation P43 FINISHED
Object TUW
TUW is the commonly used abbreviation for the Vienna University of Technology, a major technical and scientific research university in Vienna, Austria.
 E319302 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: TUW | Statement: [Vienna University of Technology, hasAbbreviation, TUW]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TUW
Context triple: [Vienna University of Technology, hasAbbreviation, TUW]
  • A. TU9
    TU9 is an alliance of nine leading German Institutes of Technology focused on engineering and natural sciences research and education.
  • B. TU
    TU is the common English abbreviation for Tohoku University, a leading national research university in Sendai, Japan.
  • C. TU
    TU is the international vehicle registration code assigned to Tunisia.
  • D. Tus
    Tus is an ancient city in northeastern Iran, renowned as a cultural and literary center and traditionally regarded as the birthplace and home of the Persian epic poet Ferdowsi.
  • E. ZTU
    ZTU is the IATA station code assigned to a specific passenger rail station in Miami, Florida, used for ticketing and travel logistics.
  • 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: TUW
Triple: [Vienna University of Technology, hasAbbreviation, TUW]
Generated description
TUW is the commonly used abbreviation for the Vienna University of Technology, a major technical and scientific research university in Vienna, Austria.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TUW
Target entity description: TUW is the commonly used abbreviation for the Vienna University of Technology, a major technical and scientific research university in Vienna, Austria.
  • A. TU9
    TU9 is an alliance of nine leading German Institutes of Technology focused on engineering and natural sciences research and education.
  • B. TU
    TU is the common English abbreviation for Tohoku University, a leading national research university in Sendai, Japan.
  • C. TU
    TU is the international vehicle registration code assigned to Tunisia.
  • D. Tus
    Tus is an ancient city in northeastern Iran, renowned as a cultural and literary center and traditionally regarded as the birthplace and home of the Persian epic poet Ferdowsi.
  • E. ZTU
    ZTU is the IATA station code assigned to a specific passenger rail station in Miami, Florida, used for ticketing and travel logistics.
  • 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_69ad8b1c4de88190a83b7cefaa1f2842 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9a11b4bc81909ce06121361b4e0f completed March 8, 2026, 3:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e4f02248190890eb3944299bd15 completed March 11, 2026, 8:56 a.m.
NEDg Description generation batch_69b12eb153b481909251dd72a7ca55d4 completed March 11, 2026, 8:58 a.m.
NED2 Entity disambiguation (via description) batch_69b1d65c9550819081e8734cece6ff13 completed March 11, 2026, 8:53 p.m.
Created at: March 8, 2026, 2:59 p.m.