Triple

T31201554
Position Surface form Disambiguated ID Type / Status
Subject Marya Mannes E795488 entity
Predicate notableWork P4 FINISHED
Object Out of My Time
Out of My Time is a memoir by American writer and social critic Marya Mannes, reflecting on her life, career, and observations of 20th-century society.
 E1950802 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: Out of My Time | Statement: [Marya Mannes, notableWork, Out of My Time]
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: Out of My Time
Triple: [Marya Mannes, notableWork, Out of My Time]
Generated description
Out of My Time is a memoir by American writer and social critic Marya Mannes, reflecting on her life, career, and observations of 20th-century society.

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_69f224d8c6608190b7882466521f62be completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69bc2ca808190876e5cb05012dbfc completed May 3, 2026, 12:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a29591e7ab48190ac54ad3e501b9b83 completed June 10, 2026, 12:31 p.m.
NEDg Description generation batch_6a295a14ff9481909756485f202d3a58 completed June 10, 2026, 12:35 p.m.
NED2 Entity disambiguation (via description) batch_6a295a8606948190ad52f1240742a2ca completed June 10, 2026, 12:37 p.m.
Created at: April 29, 2026, 9:09 p.m.