Triple

T14868763
Position Surface form Disambiguated ID Type / Status
Subject Love Parade E349684 entity
Predicate lastEditionCity P67657 FINISHED
Object Duisburg E43985 NE FINISHED

How this triple was built (3 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: Duisburg | Statement: [Love Parade, lastEditionCity, Duisburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Duisburg
Context triple: [Love Parade, lastEditionCity, Duisburg]
  • A. Duisburg chosen
    Duisburg is a major industrial and port city in western Germany’s Ruhr region, known for its steel production and one of the world’s largest inland harbors.
  • B. Düsseldorf
    Düsseldorf is a major German city on the Rhine River known for its fashion and art scenes, modern architecture, and status as an important economic and financial center.
  • C. 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.
  • D. Krefeld
    Krefeld is a city in western Germany near the Rhine River, known historically for its textile and silk industry.
  • E. Wuppertal
    Wuppertal is a city in western Germany known for its steep slopes, extensive parks, and the unique suspended monorail Wuppertal Schwebebahn.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: lastEditionCity
Context triple: [Love Parade, lastEditionCity, Duisburg]
  • A. lastEdition
    Indicates that one entity is the most recent or final edition/version within a series or sequence of editions.
  • B. previousCity
    Indicates that one city was the immediately preceding location visited or lived in before another city.
  • C. lastEditionDate
    Indicates the date on which the most recent edition or version of an item was created, published, or last updated.
  • D. lastHostCity chosen
    Indicates that one entity is the most recent city to have hosted the event or activity associated with the other entity.
  • E. firstFinalCity
    Indicates that a city is the final destination reached first in some ordered sequence of trips or routes.
  • F. None of above.

Provenance (4 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5776b848190bfe3a06ff261dc31 completed April 15, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff677b7be08190afc2767835836908 completed May 9, 2026, 4:57 p.m.
PD Predicate disambiguation batch_69de8c1798c08190b433e9ad21e41a42 completed April 14, 2026, 6:48 p.m.
Created at: April 10, 2026, 1:55 a.m.