Triple

T2465663
Position Surface form Disambiguated ID Type / Status
Subject Wimbotsham E55240 entity
Predicate hasAgriculturalLandUse P37665 FINISHED
Object true 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: true | Statement: [Wimbotsham, hasAgriculturalLandUse, true]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasAgriculturalLandUse
Context triple: [Wimbotsham, hasAgriculturalLandUse, true]
  • A. majorLandUse
    Indicates the primary way a given area of land is utilized or designated (e.g., residential, commercial, agricultural).
  • B. hasAgriculturalProduction
    Indicates that an entity engages in or is characterized by the production of agricultural goods such as crops or livestock.
  • C. otherLandUse
    Indicates that the land is used for purposes that do not fall into any of the primary or predefined land-use categories.
  • D. landUseIncludes chosen
    Indicates that a specified land area contains or permits the specified type(s) of land use within its boundaries.
  • E. primaryLandUse
    Indicates the main or dominant way in which a given piece of land is utilized or designated (e.g., residential, agricultural, commercial).
  • 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_69ab49e3622c8190ad22afa2c4fbb807 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd2bc7b5481908b3664495e99f1a4 completed March 7, 2026, 7:24 a.m.
PD Predicate disambiguation batch_69abd0b3ea308190a6d8499c2a542c50 completed March 7, 2026, 7:16 a.m.
Created at: March 6, 2026, 9:44 p.m.