Triple

T962969
Position Surface form Disambiguated ID Type / Status
Subject LaGrange, New York E20774 entity
Predicate hasLandUseCharacteristic P14072 FINISHED
Object suburban residential 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: suburban residential | Statement: [LaGrange, New York, hasLandUseCharacteristic, suburban residential]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasLandUseCharacteristic
Context triple: [LaGrange, New York, hasLandUseCharacteristic, suburban residential]
  • A. primaryLandUse chosen
    Indicates the main or dominant way in which a given piece of land is utilized or designated (e.g., residential, agricultural, commercial).
  • B. hasGeographyCharacteristic
    Indicates that an entity possesses a specific geographical feature, property, or attribute.
  • C. hasUrbanFeature
    Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
  • D. hasNearbyLandUse
    Indicates that one land area is located close to another area characterized by a specific type of land use.
  • E. neighborhoodCharacteristic
    Indicates that a particular characteristic, feature, or quality is associated with or describes a given neighborhood.
  • 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_69a493b21f2881908132dcf45dcd2f36 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b416cf4c8190bd685227db25fb53 completed March 1, 2026, 9:48 p.m.
PD Predicate disambiguation batch_69a4b2a2e23c8190b932fe88b02f995d completed March 1, 2026, 9:41 p.m.
Created at: March 1, 2026, 7:40 p.m.