Triple

T3721687
Position Surface form Disambiguated ID Type / Status
Subject Fischer E81650 entity
Predicate frequencyRankInGermany P45181 FINISHED
Object among most common surnames 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: among most common surnames in Germany | Statement: [Fischer, frequencyRankInGermany, among most common surnames in Germany]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: frequencyRankInGermany
Context triple: [Fischer, frequencyRankInGermany, among most common surnames in Germany]
  • A. rankWithinGermanStates
    Indicates the relative position or standing of an entity compared to others within the set of German federal states.
  • B. rankingInCountry chosen
    Indicates the position or level an entity holds within an ordered list specific to a particular country.
  • C. frequencyRankInUnitedStates
    Indicates the relative position of something in an ordered list based on how frequently it occurs within the United States.
  • D. chartPositionGermanSinglesChart
    Indicates the position an item reached on the German singles music chart.
  • E. countryRanking
    Indicates the relative position or rank assigned to a country within a specific ordered list or comparative evaluation.
  • 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_69ad8b1b7ef081908d2d381bbf54985a completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adca9d29208190bbf38a6aa88f954a completed March 8, 2026, 7:14 p.m.
PD Predicate disambiguation batch_69adc0436e508190909ec4a3e8443aef completed March 8, 2026, 6:30 p.m.
Created at: March 8, 2026, 3:34 p.m.