Triple

T38504285
Position Surface form Disambiguated ID Type / Status
Subject Pure E921721 entity
Predicate basedOn P98 FINISHED
Object Pure (memoir)
Pure (memoir) is a nonfiction book by Linda Kay Klein that explores the lasting psychological and spiritual effects of the American evangelical purity movement on women who grew up within it.
E2273657 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: Pure (memoir) | Statement: [Pure, basedOn, Pure (memoir)]
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: Pure (memoir)
Triple: [Pure, basedOn, Pure (memoir)]
Generated description
Pure (memoir) is a nonfiction book by Linda Kay Klein that explores the lasting psychological and spiritual effects of the American evangelical purity movement on women who grew up within it.

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_69f76ea3c5448190aa7002fc1ba3f874 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fcd265675481908e1c199e1e1eae07 completed May 7, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41d65b1de48190b25d60f7d053796a completed June 29, 2026, 2:20 a.m.
NEDg Description generation batch_6a41d9e3540c8190add45c48a8977a1f completed June 29, 2026, 2:35 a.m.
NED2 Entity disambiguation (via description) batch_6a41da4ab17c8190ab53f002ddb814aa completed June 29, 2026, 2:36 a.m.
Created at: May 3, 2026, 4:32 p.m.