Triple

T4088308
Position Surface form Disambiguated ID Type / Status
Subject Twente E87641 entity
Predicate hasRiver P165 FINISHED
Object Regge E87642 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: Regge | Statement: [Twente, hasRiver, Regge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Regge
Context triple: [Twente, hasRiver, Regge]
  • A. Regge chosen
    Regge is a small river in the eastern Netherlands that flows through the province of Overijssel and is a tributary of the Vecht.
  • B. Guralnik
    Guralnik is a surname most notably associated with American theoretical physicist Gerald Guralnik, a co-discoverer of the Higgs mechanism.
  • C. Raschi
    Raschi is an Italian surname most notably associated with Vic Raschi, a star pitcher for the New York Yankees in the late 1940s and early 1950s.
  • D. Rubbia
    Rubbia is the surname of Carlo Rubbia, an Italian physicist and Nobel laureate known for his contributions to particle physics.
  • E. Kretschmann
    Kretschmann is a German surname most prominently associated with actor Thomas Kretschmann, known for his roles in international film and television.
  • 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_69aed94425148190be337845d56fac22 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefca899008190b5ada98bdb79639f completed March 9, 2026, 5 p.m.
NED1 Entity disambiguation (via context triple) batch_69b56b6335c4819093538f261a5093b3 completed March 14, 2026, 2:06 p.m.
Created at: March 9, 2026, 3:39 p.m.