Triple

T1628515
Position Surface form Disambiguated ID Type / Status
Subject Mueller E35200 entity
Predicate hasFrequencyCharacteristic P18808 FINISHED
Object very common surname in German-speaking areas 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 common surname in German-speaking areas | Statement: [Mueller, hasFrequencyCharacteristic, very common surname in German-speaking areas]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasFrequencyCharacteristic
Context triple: [Mueller, hasFrequencyCharacteristic, very common surname in German-speaking areas]
  • A. hasFrequencyCategory
    Indicates that something is associated with a particular classification of how often it occurs or is used.
  • B. hasFrequencyNote chosen
    Indicates that something is associated with a specific note describing how often it occurs or is repeated.
  • C. hasCarrierFrequency
    Indicates that an entity (such as a signal or transmission) is associated with a specific carrier frequency at which it is transmitted or modulated.
  • D. usesFrequency
    Indicates that one entity employs or operates another entity at a specified rate, interval, or number of occurrences over time.
  • E. hasCharacteristic
    Indicates that an entity possesses, exhibits, or is defined by a particular attribute, feature, or quality.
  • 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_69a886036bc081909ff5de16dbe5e8ea completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9431af5ac8190893133f1ae490142 completed March 5, 2026, 8:47 a.m.
PD Predicate disambiguation batch_69a907c91c888190b6ed295c1a2e0977 completed March 5, 2026, 4:34 a.m.
Created at: March 4, 2026, 7:28 p.m.