Triple

T20087532
Position Surface form Disambiguated ID Type / Status
Subject Masaryk Square in Hradec Králové E496173 entity
Predicate hasSurroundingBuildingsUse P52857 FINISHED
Object administrative buildings 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: administrative buildings | Statement: [Masaryk Square in Hradec Králové, hasSurroundingBuildingsUse, administrative buildings]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasSurroundingBuildingsUse
Context triple: [Masaryk Square in Hradec Králové, hasSurroundingBuildingsUse, administrative buildings]
  • A. hasNeighboringBuilding
    Indicates that one building is located adjacent to or directly next to another building.
  • B. hasBuildingStyleInSurroundings chosen
    Indicates that an entity is surrounded by or located in an area characterized by a particular building style.
  • C. hasNearbyLandUse
    Indicates that one land area is located close to another area characterized by a specific type of land use.
  • D. hasSurroundings
    Indicates that an entity is located within or encircled by a particular environment, context, or set of surrounding elements.
  • E. floorCountOfSurroundingBuildings
    Indicates the number of floors in the buildings that are located around or near a given reference building or area.
  • 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_69da626eee3881909f3454986d4a6511 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6655c7de081909a400c736e92495d completed April 20, 2026, 5:41 p.m.
PD Predicate disambiguation batch_69e54cf369b88190931532420517dac7 completed April 19, 2026, 9:45 p.m.
Created at: April 11, 2026, 11:13 p.m.