Triple

T3375627
Position Surface form Disambiguated ID Type / Status
Subject New York State Multiple Use Areas E71059 entity
Predicate landUseType P38195 FINISHED
Object multiple use 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: multiple use | Statement: [New York State Multiple Use Areas, landUseType, multiple use]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: landUseType
Context triple: [New York State Multiple Use Areas, landUseType, multiple use]
  • A. landUseIncludes
    Indicates that a specified land area contains or permits the specified type(s) of land use within its boundaries.
  • B. majorLandUse chosen
    Indicates the primary way a given area of land is utilized or designated (e.g., residential, commercial, agricultural).
  • C. primaryLandUse
    Indicates the main or dominant way in which a given piece of land is utilized or designated (e.g., residential, agricultural, commercial).
  • D. otherLandUse
    Indicates that the land is used for purposes that do not fall into any of the primary or predefined land-use categories.
  • E. formerLandUse
    Indicates the type of land use that characterized a location prior to its current or present use.
  • 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_69ad85a7f80c8190a05e43013f298942 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb2e5fc6c81909ff582611751096d completed March 8, 2026, 5:33 p.m.
PD Predicate disambiguation batch_69ada433059881908e46f38cc5f40a32 completed March 8, 2026, 4:30 p.m.
Created at: March 8, 2026, 3:13 p.m.