Triple

T30397164
Position Surface form Disambiguated ID Type / Status
Subject Greendale Fault E773248 entity
Predicate crossesLandUseType P179237 FINISHED
Object agricultural land 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: agricultural land | Statement: [Greendale Fault, crossesLandUseType, agricultural land]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: crossesLandUseType
Context triple: [Greendale Fault, crossesLandUseType, agricultural land]
  • A. servesLandUseType
    Indicates that one entity functions to support, accommodate, or provide services for a specified land use type.
  • B. otherLandUse
    Indicates that the land is used for purposes that do not fall into any of the primary or predefined land-use categories.
  • C. majorLandUse
    Indicates the primary way a given area of land is utilized or designated (e.g., residential, commercial, agricultural).
  • D. landUseIncludes
    Indicates that a specified land area contains or permits the specified type(s) of land use within its boundaries.
  • E. hasLandUseCharacter
    Indicates that one entity possesses or is associated with a particular type or pattern of land use.
  • F. None of above. chosen

Provenance (4 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_69f2248facd48190b183c3f3ca6daef7 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f7201e241c819092d56a7bb99dc94d completed May 3, 2026, 10:14 a.m.
PD Predicate disambiguation batch_69f71cc405c08190863565609a4c8499 completed May 3, 2026, 10 a.m.
PDg Predicate description generation batch_69f71f8df5d48190944fbfbd9d573868 completed May 3, 2026, 10:12 a.m.
Created at: April 29, 2026, 8:03 p.m.