Triple

T16531357
Position Surface form Disambiguated ID Type / Status
Subject Lundenwic E401572 entity
Predicate urbanCharacteristics P9356 FINISHED
Object planned street system (partly reconstructed) 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: planned street system (partly reconstructed) | Statement: [Lundenwic, urbanCharacteristics, planned street system (partly reconstructed)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: urbanCharacteristics
Context triple: [Lundenwic, urbanCharacteristics, planned street system (partly reconstructed)]
  • A. neighborhoodCharacteristic chosen
    Indicates that a particular characteristic, feature, or quality is associated with or describes a given neighborhood.
  • B. urbanAreaType
    Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, metropolitan region).
  • C. hasSuburbanCharacter
    Indicates that something possesses qualities or features typically associated with suburban areas, such as lower density, residential focus, and car-oriented development.
  • D. hasUrbanGrowthCharacteristic
    Indicates that an entity exhibits a particular quality, pattern, or feature related to urban growth or expansion.
  • E. urbanContrastWith
    Indicates a contrast or sharp difference between two urban environments, such as in character, form, density, or visual appearance.
  • 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_69d883838abc8190bc79cb2d41733ce2 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32ed8075c81908ff47396879abd0c completed April 18, 2026, 7:12 a.m.
PD Predicate disambiguation batch_69e296995d388190b88ebe189dce890d completed April 17, 2026, 8:22 p.m.
Created at: April 10, 2026, 5:14 a.m.