Triple

T31717511
Position Surface form Disambiguated ID Type / Status
Subject Eileen Myles E809488 entity
Predicate notableWork P4 FINISHED
Object Inferno: A Poet’s Novel
Inferno: A Poet’s Novel is an experimental, autobiographical novel by poet Eileen Myles that blends prose and poetry to chronicle their coming-of-age and artistic life in New York’s downtown literary scene.
 E1972715 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: Inferno: A Poet’s Novel | Statement: [Eileen Myles, notableWork, Inferno: A Poet’s Novel]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Inferno: A Poet’s Novel
Triple: [Eileen Myles, notableWork, Inferno: A Poet’s Novel]
Generated description
Inferno: A Poet’s Novel is an experimental, autobiographical novel by poet Eileen Myles that blends prose and poetry to chronicle their coming-of-age and artistic life in New York’s downtown literary scene.

Provenance (5 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_69f348df4e048190a4a5a9932ada78d6 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6aaf50be08190a2b62a6d881f8aee completed May 3, 2026, 1:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b84d50e1481909137909a939acdb5 completed June 12, 2026, 4:02 a.m.
NEDg Description generation batch_6a2b8567556c8190ad273a1cdf8a11cf completed June 12, 2026, 4:04 a.m.
NED2 Entity disambiguation (via description) batch_6a2b8598ebb481909235beb350564bce completed June 12, 2026, 4:05 a.m.
Created at: April 30, 2026, 11:17 p.m.