Triple

T20206359
Position Surface form Disambiguated ID Type / Status
Subject Bodenseekreis E493361 entity
Predicate hasMunicipality P847 FINISHED
Object Meersburg NE NERFINISHED

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: Meersburg | Statement: [Bodenseekreis, hasMunicipality, Meersburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meersburg
Context triple: [Bodenseekreis, hasMunicipality, Meersburg]
  • A. Meersburg chosen
    Meersburg is a historic town in southern Germany known for its medieval castle, picturesque old town, and scenic location on the shores of Lake Constance.
  • B. Speyer
    Speyer is a historic city in southwestern Germany on the Rhine River, renowned for its Romanesque imperial cathedral, a UNESCO World Heritage Site.
  • C. Spassburg
    Spassburg is the German-themed area of the Six Flags Fiesta Texas amusement park, featuring rides, shops, and architecture inspired by traditional German towns.
  • D. Müggelheim
    Müggelheim is a village-like district in the southeastern part of Berlin, Germany, characterized by its forests, lakes, and tranquil, semi-rural atmosphere.
  • E. Landsberg
    Landsberg is a town in the Saalekreis district of the German state of Saxony-Anhalt.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6269614c8190bb40475d9d477358 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66d922ebc8190ae012da8ceba74dd completed April 20, 2026, 6:16 p.m.
Created at: April 11, 2026, 11:38 p.m.