Triple

T35605788
Position Surface form Disambiguated ID Type / Status
Subject The End of the Whole Mess E1028886 entity
Predicate mainCharacter P1183 FINISHED
Object Howard Fornoy
Howard Fornoy is the narrator and central figure of Stephen King’s apocalyptic short story "The End of the Whole Mess," recounting his brother’s well-intentioned experiment that leads to global catastrophe.
E2156081 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: Howard Fornoy | Statement: [The End of the Whole Mess, mainCharacter, Howard Fornoy]
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: Howard Fornoy
Triple: [The End of the Whole Mess, mainCharacter, Howard Fornoy]
Generated description
Howard Fornoy is the narrator and central figure of Stephen King’s apocalyptic short story "The End of the Whole Mess," recounting his brother’s well-intentioned experiment that leads to global catastrophe.

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_69f76e0653ec81909b1b813c126c6574 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79ec6408081908e8a1eee79363cb0 completed May 3, 2026, 7:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38914dc2a4819082b8d704c262f72c completed June 22, 2026, 1:35 a.m.
NEDg Description generation batch_6a38922d9814819089669865036c8474 completed June 22, 2026, 1:38 a.m.
NED2 Entity disambiguation (via description) batch_6a3892ae3d608190b6594f287fa7ff6d completed June 22, 2026, 1:41 a.m.
Created at: May 3, 2026, 4:05 p.m.