Triple

T31631464
Position Surface form Disambiguated ID Type / Status
Subject Funtensee E807176 entity
Predicate hasExtremeTemperatureRecord P15651 FINISHED
Object very low minimum temperatures in Germany LITERAL 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: very low minimum temperatures in Germany | Statement: [Funtensee, hasExtremeTemperatureRecord, very low minimum temperatures in Germany]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasExtremeTemperatureRecord
Context triple: [Funtensee, hasExtremeTemperatureRecord, very low minimum temperatures in Germany]
  • A. maximumRecordedTemperature
    Indicates the highest temperature value that has been observed and recorded for a given entity or context.
  • B. notableWeather
    Indicates that a location experiences weather conditions that are significant, unusual, or noteworthy in some way.
  • C. recordLowTemperature chosen
    Indicates that a specified temperature value is the lowest recorded temperature for a given entity, location, or time period.
  • D. hasHighestTemperature
    Indicates that the referenced entity possesses the greatest temperature value compared to all other relevant entities in the given context.
  • E. recordHighTemperatureLocation
    Indicates the location where the highest recorded temperature occurred.
  • F. None of above.

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_69f348d892948190915f8facacb9568c completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f791cc969c8190bf187d6031a030d5 completed May 3, 2026, 6:19 p.m.
PD Predicate disambiguation batch_69f791033d288190b118029fe412b9c9 completed May 3, 2026, 6:16 p.m.
Created at: April 30, 2026, 10:45 p.m.