Triple

T11467128
Position Surface form Disambiguated ID Type / Status
Subject UEFA Euro 1988 matches E271806 entity
Predicate hostCity P1798 FINISHED
Object Gelsenkirchen E167466 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: Gelsenkirchen | Statement: [UEFA Euro 1988 matches, hostCity, Gelsenkirchen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gelsenkirchen
Context triple: [UEFA Euro 1988 matches, hostCity, Gelsenkirchen]
  • A. Gelsenkirchen chosen
    Gelsenkirchen is a city in western Germany known for its strong football culture and modern stadium, Veltins-Arena, home to FC Schalke 04.
  • B. Recklinghausen
    Recklinghausen is a city in the Ruhr area of North Rhine-Westphalia, western Germany, known historically for coal mining and its role as a regional administrative center.
  • C. Remscheid
    Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
  • D. Mülheim an der Ruhr
    Mülheim an der Ruhr is a city in western Germany’s Ruhr area, known for its industrial heritage, riverside setting on the Ruhr River, and role as a regional economic and cultural center.
  • E. Bochum
    Bochum is a major city in Germany’s Ruhr region known for its industrial heritage, cultural institutions, and large university.
  • 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_69d6aae0c8d881908a5a360c0be3242e completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d822f5eb988190b309b8e309f6d1a5 completed April 9, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62a7133d88190813a1e74ef310993 completed May 2, 2026, 4:46 p.m.
Created at: April 8, 2026, 9:35 p.m.