Triple

T976065
Position Surface form Disambiguated ID Type / Status
Subject Warning E21054 entity
Predicate hasPart P35 FINISHED
Object Misery E37480 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: Misery | Statement: [Warning, hasPart, Misery]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Misery
Context triple: [Warning, hasPart, Misery]
  • A. Misery
    Misery is the first major section of the Heidelberg Catechism, focusing on humanity’s sinfulness and need for redemption.
  • B. Misery chosen
    Misery is a psychological horror novel by Stephen King about a famous author held captive by his deranged “number one fan.”
  • C. Carrie
    "Carrie" is Stephen King's debut horror novel, centered on a bullied teenage girl with telekinetic powers who exacts a devastating revenge on her tormentors.
  • D. Gone
    "Gone" is a reflective hip-hop track by Kanye West featuring Consequence and Cam'ron, known for its soulful Otis Redding sample and intricate storytelling.
  • E. The Shining
    The Shining is a 1977 horror novel by Stephen King that follows a troubled writer who becomes the winter caretaker of an isolated, malevolent hotel that slowly drives him to madness.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a493c2b62c8190b616351789ec47f8 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b46234c88190b2bfc9cafe59d7f7 completed March 1, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac170c0fdc8190b904ca5737764f5a completed March 7, 2026, 12:16 p.m.
Created at: March 1, 2026, 7:40 p.m.