Triple

T1009832
Position Surface form Disambiguated ID Type / Status
Subject Ezra Pound E21795 entity
Predicate wroteTextOn P2831 FINISHED
Object literary theory 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: literary theory | Statement: [Ezra Pound, wroteTextOn, literary theory]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: wroteTextOn
Context triple: [Ezra Pound, wroteTextOn, literary theory]
  • A. areWrittenOn
    Indicates that one entity serves as a surface or medium on which another entity is inscribed, recorded, or written.
  • B. wroteIn
    Indicates that an entity authored or composed something using a particular language, medium, or writing system.
  • C. wrote chosen
    Indicates that an entity is the author or creator of a written work involving another entity.
  • D. writtenIn
    Indicates that a work (such as a text, program, or document) is expressed or encoded using a particular language or notation.
  • E. hasWrittenFor
    Indicates that one entity has created written content (such as articles, stories, or texts) for or on behalf of another entity, typically a publication, organization, or platform.
  • 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_69a493c53e648190ae8cb76c433fd9a7 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b7f4c66c8190b6098fb72c1465a3 completed March 1, 2026, 10:04 p.m.
PD Predicate disambiguation batch_69a4b7203124819091de68cba5f731c1 completed March 1, 2026, 10:01 p.m.
Created at: March 1, 2026, 7:41 p.m.