Triple

T12235923
Position Surface form Disambiguated ID Type / Status
Subject Filbert Street E291590 entity
Predicate zoningSecondaryUse P23955 FINISHED
Object office 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: office | Statement: [Filbert Street, zoningSecondaryUse, office]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: zoningSecondaryUse
Context triple: [Filbert Street, zoningSecondaryUse, office]
  • A. secondaryLandUse chosen
    Indicates a secondary or additional way in which a piece of land is used, beyond its primary designated use.
  • B. hasIndustrialZoning
    Indicates that a given area or property is designated for industrial use under zoning regulations.
  • C. associatedWithVenueSecondaryUse
    Indicates that an entity has a secondary or supplementary association with a particular venue, beyond its primary or main use.
  • D. hasZoningRestriction
    Indicates that an entity is subject to a specific zoning-related limitation or regulatory constraint.
  • E. landUseIncludes
    Indicates that a specified land area contains or permits the specified type(s) of land use within its boundaries.
  • 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_69d6ab668acc8190963ba424049d6aee completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d924a3973c8190a882046963b320fb completed April 10, 2026, 4:26 p.m.
PD Predicate disambiguation batch_69d91c41bcbc81909782f4e3c571b218 completed April 10, 2026, 3:50 p.m.
Created at: April 8, 2026, 9:51 p.m.