Triple

T14023046
Position Surface form Disambiguated ID Type / Status
Subject Virginia Center Commons area E337382 entity
Predicate parkingPattern P3380 FINISHED
Object surface parking lots 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: surface parking lots | Statement: [Virginia Center Commons area, parkingPattern, surface parking lots]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: parkingPattern
Context triple: [Virginia Center Commons area, parkingPattern, surface parking lots]
  • A. parkingType chosen
    Indicates the specific kind or category of parking arrangement associated with an entity (e.g., street, garage, lot, reserved).
  • B. parkingOften
    Indicates that an entity frequently engages in the action of parking, or that parking occurs often in relation to that entity.
  • C. parkingStructure
    Indicates that one entity is a parking facility or structure associated with another entity (such as a building, location, or organization).
  • D. parkSystem
    Indicates a relationship where an entity is part of, managed by, or associated with an organized system of parks or protected recreational areas.
  • E. parkingRequirement
    Indicates the specified conditions or obligations related to providing or using parking associated with an entity or activity.
  • 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_69d81c6543a48190bd5ba93d7419e797 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2f3d87b88190b038d334f4965369 completed April 14, 2026, 12:12 p.m.
PD Predicate disambiguation batch_69de05a802ac819090604025aae6a4d5 completed April 14, 2026, 9:15 a.m.
Created at: April 9, 2026, 10:19 p.m.