Triple

T10988164
Position Surface form Disambiguated ID Type / Status
Subject Kitzingen (district) E259684 entity
Predicate hasMunicipality P847 FINISHED
Object Marktbreit E494094 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: Marktbreit | Statement: [Kitzingen (district), hasMunicipality, Marktbreit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marktbreit
Context triple: [Kitzingen (district), hasMunicipality, Marktbreit]
  • A. Marktbreit chosen
    Marktbreit is a small historic town in Bavaria, Germany, best known as the birthplace of psychiatrist and neuropathologist Alois Alzheimer.
  • B. Marktl
    Marktl is a small Bavarian municipality best known as the birthplace of Pope Benedict XVI.
  • C. Mülbracht
    Mülbracht is a historical locality in the Holy Roman Empire known primarily as the birthplace of the Dutch Golden Age engraver and painter Hendrick Goltzius.
  • D. Brannenburg
    Brannenburg is a Bavarian municipality in southern Germany, known for its scenic Alpine setting and outdoor recreation opportunities.
  • E. Brackenheim
    Brackenheim is a small town in the German state of Baden-Württemberg, best known as the birthplace of Theodor Heuss, the first President of the Federal Republic of Germany.
  • 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_69d6aa8a6a548190a750f944ccdc8064 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d787b574d08190adec34b814a26437 completed April 9, 2026, 11:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69e344f95ab88190bbce8f0eab0b2713 completed April 18, 2026, 8:46 a.m.
Created at: April 8, 2026, 9:24 p.m.