Triple

T23335518
Position Surface form Disambiguated ID Type / Status
Subject Willa Cather Foundation E591568 entity
Predicate hasDonatedTheme P151906 FINISHED
Object preservation of cultural heritage 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: preservation of cultural heritage | Statement: [Willa Cather Foundation, hasDonatedTheme, preservation of cultural heritage]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasDonatedTheme
Context triple: [Willa Cather Foundation, hasDonatedTheme, preservation of cultural heritage]
  • A. hasThemeType
    Indicates that something is associated with or characterized by a particular thematic category or type.
  • B. hasPersonalThemes
    Indicates that something (such as a work, message, or expression) involves themes that are personal, intimate, or directly related to an individual’s own experiences or inner life.
  • C. hasMotiveTheme
    Indicates that an action, event, or situation is associated with a central motivating theme or underlying driving idea.
  • D. hasThemeConnection
    Indicates a relationship where one entity is linked to another through a shared or related theme, topic, or conceptual focus.
  • E. hasThemeInStory
    Indicates that a particular theme is present or plays a significant role within a given story.
  • 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_69e25d20156c81908c5c53195bd9c738 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f197f08fe481908766e674164d6d45 completed April 29, 2026, 5:32 a.m.
PD Predicate disambiguation batch_69effcf8ca2c8190887d4f4656617d21 completed April 28, 2026, 12:19 a.m.
PDg Predicate description generation batch_69f01d88b4ec8190a2a17a88e0eda178 completed April 28, 2026, 2:38 a.m.
Created at: April 17, 2026, 5:16 p.m.