Triple

T32955704
Position Surface form Disambiguated ID Type / Status
Subject Leonberg town hall E843092 entity
Predicate hasMunicipalCodeArea P194318 FINISHED
Object Baden-Württemberg 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: Baden-Württemberg | Statement: [Leonberg town hall, hasMunicipalCodeArea, Baden-Württemberg]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMunicipalCodeArea
Context triple: [Leonberg town hall, hasMunicipalCodeArea, Baden-Württemberg]
  • A. hasMunicipalityCode
    Indicates that an entity is associated with a specific official municipality code used for administrative or identification purposes.
  • B. hasMunicipalCodeJurisdiction
    Indicates that an authority or entity holds official legal or regulatory power within a specific municipal code area or jurisdiction.
  • C. hasMunicipalCodeCountry
    Indicates that a municipal code is associated with, or belongs to, a specific country.
  • D. hasMunicipalCodeAuthority
    Indicates that an entity has the official power or jurisdiction to create, adopt, or enforce municipal codes, ordinances, or regulations.
  • E. hasMunicipalUnitArea
    Indicates that a municipal unit is associated with a specific measured area.
  • F. None of above. chosen

Provenance (4 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_69f3494a31f481909057136e49b4fe60 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69fd6a1c1c4881908090053bc359b181 completed May 8, 2026, 4:44 a.m.
PD Predicate disambiguation batch_69fd696f24d8819091033afacbdaadc5 completed May 8, 2026, 4:41 a.m.
PDg Predicate description generation batch_69fd6a1a38f081908c573aee4696de4f completed May 8, 2026, 4:44 a.m.
Created at: May 1, 2026, 1:21 a.m.