Triple

T14448907
Position Surface form Disambiguated ID Type / Status
Subject 4TU.Federation E358279 entity
Predicate abbreviation P43 FINISHED
Object 4TU E358279 NE FINISHED

How this triple was built (2 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: 4TU | Statement: [4TU.Federation, abbreviation, 4TU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 4TU
Context triple: [4TU.Federation, abbreviation, 4TU]
  • A. 4TU.Federation chosen
    4TU.Federation is a collaborative alliance of four Dutch technical universities focused on strengthening and coordinating engineering and technology education and research in the Netherlands.
  • B. TUW
    TUW is the commonly used abbreviation for the Vienna University of Technology, a major technical and scientific research university in Vienna, Austria.
  • C. ZTU
    ZTU is the IATA station code assigned to a specific passenger rail station in Miami, Florida, used for ticketing and travel logistics.
  • D. TUDa
    TUDa is a leading German research university located in Darmstadt, renowned for its engineering, computer science, and natural sciences programs.
  • E. TUK
    TUK is the abbreviation for the Technical University of Kaiserslautern, a German public research university known for its strong engineering and science programs.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d82794dfa081909b9134ad2e32244b completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de916139888190be219678e29a2a3a completed April 14, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bdf451c8190baaa3f7500eaea16 completed May 8, 2026, 3:43 a.m.
Created at: April 10, 2026, 1:19 a.m.