Triple

T967099
Position Surface form Disambiguated ID Type / Status
Subject Täby Municipality E20860 entity
Predicate hasMunicipalCode P3943 FINISHED
Object 0160 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: 0160 | Statement: [Täby Municipality, hasMunicipalCode, 0160]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMunicipalCode
Context triple: [Täby Municipality, hasMunicipalCode, 0160]
  • A. hasMunicipalityCode chosen
    Indicates that an entity is associated with a specific official municipality code used for administrative or identification purposes.
  • B. hasMunicipalityType
    Indicates that an administrative unit is classified as having a specific type or category of municipality (e.g., city, town, village).
  • C. hasMunicipalGovernment
    Indicates that an entity is administered or governed by a municipal-level governmental authority.
  • D. isInMunicipality
    Indicates that one entity (typically a place or address) is located within the administrative boundaries of a specific municipality.
  • E. hasMunicipalSections
    Indicates that a municipality is divided into and associated with specific internal administrative sections or districts.
  • 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_69a493b33d2c81909c52c369d3ca8436 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b43412488190b68e33d2b36a0ba3 completed March 1, 2026, 9:48 p.m.
PD Predicate disambiguation batch_69a4b2a42c1481908d940cbe0aefdd3b completed March 1, 2026, 9:41 p.m.
Created at: March 1, 2026, 7:40 p.m.