Triple

T6379607
Position Surface form Disambiguated ID Type / Status
Subject Mayer E143547 entity
Predicate hasVariant P455 FINISHED
Object Maier E345534 NE 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: Maier | Statement: [Mayer, hasVariant, Maier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maier
Context triple: [Mayer, hasVariant, Maier]
  • A. Meier
    Meier is a common German surname borne by numerous individuals across various professions and regions.
  • B. Meyer
    Meyer is a given name most famously associated with Meyer Lansky, a major organized crime figure in the United States during the 20th century.
  • C. Meyer chosen
    Meyer is a common German-origin surname borne by numerous notable individuals across fields such as literature, entertainment, sports, and academia.
  • D. Maufe
    Maufe is a surname most notably associated with Sir Edward Maufe, a 20th-century British architect known for designing Guildford Cathedral and several prominent war memorials.
  • E. Mieresch
    Mieresch is the German name for the Mureș River, a major river flowing through Romania and Hungary.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69c008d9f4348190ab598a2913259a1c completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0685029488190911fb24c470b6f0d completed March 22, 2026, 10:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69c62daf2f408190923d67bd0222d2bb completed March 27, 2026, 7:11 a.m.
Created at: March 22, 2026, 4:33 p.m.