Triple

T2113090
Position Surface form Disambiguated ID Type / Status
Subject Weeks E42546 entity
Predicate agriculturalAspect P25683 FINISHED
Object wheat harvest in the Land of Israel 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: wheat harvest in the Land of Israel | Statement: [Weeks, agriculturalAspect, wheat harvest in the Land of Israel]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: agriculturalAspect
Context triple: [Weeks, agriculturalAspect, wheat harvest in the Land of Israel]
  • A. agriculturalPractice
    Indicates a relationship where an entity engages in, applies, or is associated with a specific method or technique of agriculture or farming.
  • B. agriculturalRole
    Indicates a role or function that an entity has within agricultural activities, production, or systems.
  • C. farmingCharacteristics
    Indicates the specific methods, practices, or attributes that characterize how farming is conducted in relation to an entity.
  • D. hasAgriculturalProduction chosen
    Indicates that an entity engages in or is characterized by the production of agricultural goods such as crops or livestock.
  • E. crop
    Indicates the action of cutting or trimming part of an object or image, typically to remove unwanted outer areas while keeping a selected region.
  • 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_69a8871040f08190aac2e2d0ab6b47ad completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abbb0495d0819097dc936540743b74 completed March 7, 2026, 5:43 a.m.
PD Predicate disambiguation batch_69abb7ba08948190a3c236bb53ee4257 completed March 7, 2026, 5:29 a.m.
Created at: March 4, 2026, 7:43 p.m.