Triple

T3385187
Position Surface form Disambiguated ID Type / Status
Subject Robert Lowell E71282 entity
Predicate movement P81 FINISHED
Object Confessional poetry E62688 NE 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: Confessional poetry | Statement: [Robert Lowell, movement, Confessional poetry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Confessional poetry
Context triple: [Robert Lowell, movement, Confessional poetry]
  • A. Confessional poetry chosen
    Confessional poetry is a style of verse that foregrounds intimate, often painful personal experience—such as mental illness, trauma, and family conflict—using a candid, autobiographical voice.
  • B. Projective Verse
    Projective Verse is Charles Olson’s influential 1950 essay that outlines a breath-based, open-form poetics central to the practice and theory of the Black Mountain poets.
  • C. Poetry
    Poetry is a Python dependency management and packaging tool that simplifies creating, building, and publishing Python projects.
  • D. Poetic
    Poetic was an American rapper best known as a member of the influential horrorcore group Gravediggaz.
  • E. Sonnets
    Sonnets is a celebrated collection of 154 lyric poems by William Shakespeare that explore themes such as love, beauty, time, and mortality.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ad85a8fd9c819095ecedf838d2bf1b completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb5ee5e188190912dcea494a12038 completed March 8, 2026, 5:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b33455ae2481908e6478cb240b31c1 completed March 12, 2026, 9:47 p.m.
Created at: March 8, 2026, 3:14 p.m.