Triple

T18499944
Position Surface form Disambiguated ID Type / Status
Subject Dialogue of Comfort against Tribulation E452040 entity
Predicate literaryStructure P22618 FINISHED
Object two books 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: two books | Statement: [Dialogue of Comfort against Tribulation, literaryStructure, two books]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: literaryStructure
Context triple: [Dialogue of Comfort against Tribulation, literaryStructure, two books]
  • A. textualStructure chosen
    Indicates how parts of a text are organized and related to each other within its overall structure.
  • B. literaryFeature
    Indicates a relationship where something possesses or exhibits a characteristic, device, or stylistic element used in literature.
  • C. literaryUnit
    Indicates that one entity is a distinct segment or component (such as a chapter, scene, or passage) within a larger literary work or text.
  • D. poeticStructure
    Indicates a relationship where one entity defines, embodies, or specifies the formal poetic organization (such as meter, rhyme scheme, or stanza pattern) used by another entity.
  • E. literaryScript
    Indicates a relationship where an entity serves as the written text or script of a literary work, such as a play, film, or other narrative production.
  • 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_69d8d3855d50819097fc8561b0299dd9 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e532c3810c81908fa329c177c6d96c completed April 19, 2026, 7:53 p.m.
PD Predicate disambiguation batch_69e469dbf5208190b6fc49e02a087f54 completed April 19, 2026, 5:36 a.m.
Created at: April 10, 2026, 11:36 a.m.