Triple

T14996351
Position Surface form Disambiguated ID Type / Status
Subject Waldstadion E373966 entity
Predicate ownedBy P347 FINISHED
Object City of Frankfurt am Main E16481 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: City of Frankfurt am Main | Statement: [Waldstadion, ownedBy, City of Frankfurt am Main]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Frankfurt am Main
Context triple: [Waldstadion, ownedBy, City of Frankfurt am Main]
  • A. Frankfurt am Main chosen
    Frankfurt am Main is a major German financial and transportation hub on the River Main, known for hosting the European Central Bank and one of Europe’s busiest airports.
  • B. Oper Frankfurt
    Oper Frankfurt is a major German opera house in Frankfurt am Main, renowned for its high artistic standards and innovative productions.
  • C. Frankfurt Rhine-Main
    Frankfurt Rhine-Main is a major metropolitan region in western Germany centered around Frankfurt am Main, known as a key European hub for finance, transportation, and commerce.
  • D. Wiesbaden
    Wiesbaden is a historic spa city in western Germany known for its thermal springs, elegant architecture, and role as a regional administrative and cultural center.
  • E. Stadt Nürnberg
    Stadt Nürnberg is the municipal government of the German city of Nuremberg, responsible for local administration, public services, and urban infrastructure.
  • 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded718e4288190b5e144f82299a194 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69feae080ef88190a26c4f9b1675f9de completed May 9, 2026, 3:46 a.m.
Created at: April 10, 2026, 2:53 a.m.