Triple

T20642989
Position Surface form Disambiguated ID Type / Status
Subject Deutsche Messe AG E507276 entity
Predicate hasNotableEvent P259 FINISHED
Object Interschutz 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: Interschutz | Statement: [Deutsche Messe AG, hasNotableEvent, Interschutz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Interschutz
Context triple: [Deutsche Messe AG, hasNotableEvent, Interschutz]
  • A. Interschutz chosen
    Interschutz is a major international trade fair focused on firefighting, rescue services, civil protection, and safety/security technologies.
  • B. Steyer
    Steyer is a Polish surname most notably borne by Włodzimierz Steyer, a Polish naval officer and admiral.
  • C. Speer
    Speer is a German surname most famously associated with Albert Speer, the Nazi architect and Minister of Armaments and War Production during World War II.
  • D. Arbizon
    Arbizon is a prominent peak in the French Pyrenees known for its striking pyramidal shape and panoramic views over the surrounding valleys.
  • E. Ilster
    The Ilster is a small river in Lower Saxony, Germany, known as one of the headwater streams contributing to the Örtze river system.
  • 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_69e0b4be702c8190a3d2410a881d310a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6af1c51f48190abba54a5aace9fc8 completed April 20, 2026, 10:56 p.m.
Created at: April 16, 2026, 11:43 a.m.