Triple

T17357223
Position Surface form Disambiguated ID Type / Status
Subject DEG Metro Stars E421969 entity
Predicate shortName P43 FINISHED
Object DEG 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: DEG | Statement: [DEG Metro Stars, shortName, DEG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DEG
Context triple: [DEG Metro Stars, shortName, DEG]
  • A. DEG chosen
    DEG is a professional ice hockey club based in Düsseldorf, Germany, competing in the country’s top-tier league and known for its rich history and multiple championship titles.
  • B. DEG
    DEG is the vehicle registration code used for cars registered in the town of Plattling in Bavaria, Germany.
  • C. DEGES
    DEGES is a former German project management company responsible for planning and building major federal transport infrastructure, particularly motorways and highways.
  • D. DEGS
    DEGS is a large-scale, nationally representative health survey conducted in Germany to monitor the population’s health status, risk factors, and healthcare utilization over time.
  • E. DEE
    DEE is the IATA airport code for Yuzhno-Kurilsk Mendeleyevo Airport, which serves the town of Yuzhno-Kurilsk in Russia’s Kuril Islands.
  • 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_69d889d520008190a26917a95bf1c2ea completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a4976788190b00c00f710be6c46 completed April 19, 2026, 2:13 a.m.
Created at: April 10, 2026, 5:44 a.m.