Triple

T18684028
Position Surface form Disambiguated ID Type / Status
Subject Gdańsk University of Technology E456808 entity
Predicate shortName P43 FINISHED
Object GUT NE NERFINISHED

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: GUT | Statement: [Gdańsk University of Technology, shortName, GUT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GUT
Context triple: [Gdańsk University of Technology, shortName, GUT]
  • A. GUT chosen
    GUT is a leading technical university in Gdańsk, Poland, known for its engineering, technology, and research programs.
  • B. Gut
    Gut is a surname of Germanic origin borne by various individuals, including the Czech ice hockey player and coach Karel Gut.
  • C. GI
    GI is the vehicle registration code used on license plates for the German city of Gießen in the state of Hesse.
  • D. Dry Gut
    Dry Gut is a steep-sided valley or ravine on the island of Saint Helena, known for its stark, barren terrain and proximity to the Prosperous Bay Plain plateau.
  • E. Gutach
    Gutach is a river in the Black Forest region of Baden-Württemberg, Germany, known for flowing from the Titisee and passing scenic valleys and waterfalls before joining the Kinzig.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d391eb488190ac2e9abf5bf255e4 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e55b2b819c8190b5f3d7a88607f6f5 completed April 19, 2026, 10:46 p.m.
Created at: April 10, 2026, 11:49 a.m.