Triple

T32904749
Position Surface form Disambiguated ID Type / Status
Subject Cold Print E841704 entity
Predicate hasSetting P3538 FINISHED
Object Severn Valley (fictional setting)
Severn Valley is a fictional, Lovecraftian-inspired region in England used as a recurring horror setting in the works of Ramsey Campbell.
E2027820 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: Severn Valley (fictional setting) | Statement: [Cold Print, hasSetting, Severn Valley (fictional setting)]
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: Severn Valley (fictional setting)
Triple: [Cold Print, hasSetting, Severn Valley (fictional setting)]
Generated description
Severn Valley is a fictional, Lovecraftian-inspired region in England used as a recurring horror setting in the works of Ramsey Campbell.

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_69f34946a5208190bbd79f0fec4323bd completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d07ca49c8190a3833a874a807895 completed May 3, 2026, 4:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34c694812881908ca927ebb49d60c3 completed June 19, 2026, 4:33 a.m.
NEDg Description generation batch_6a34c84409a88190a8eaaf78b0fa0666 completed June 19, 2026, 4:40 a.m.
NED2 Entity disambiguation (via description) batch_6a34c93dd1d48190b67b29c885246998 completed June 19, 2026, 4:44 a.m.
Created at: May 1, 2026, 1:19 a.m.