Triple

T31734566
Position Surface form Disambiguated ID Type / Status
Subject The Black Book E809956 entity
Predicate centralMysteryType P25900 FINISHED
Object cold case LITERAL 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: cold case | Statement: [The Black Book, centralMysteryType, cold case]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: centralMysteryType
Context triple: [The Black Book, centralMysteryType, cold case]
  • A. centralMystery chosen
    Indicates that something serves as the primary unresolved question or puzzle around which a narrative, situation, or investigation is structured.
  • B. mysteryAssociatedWith
    Indicates a relationship where something is connected to, involved in, or characterized by an element of mystery or the unknown.
  • C. thirdMystery
    Indicates a relationship where an entity is associated with the third mystery in a defined ordered set of mysteries (such as stages, secrets, or thematic elements).
  • D. secondMystery
    Indicates a secondary, less obvious or more enigmatic relationship or phenomenon whose nature is not immediately clear or explicitly defined.
  • E. focusesOnMysteries
    Indicates that the subject concentrates attention or effort specifically on mysteries, such as puzzling events, unknown phenomena, or unsolved cases.
  • F. None of above.

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_69f348e0e4908190a884582eca646fb7 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69fcdf2394748190b35cead3e208447d completed May 7, 2026, 6:51 p.m.
PD Predicate disambiguation batch_69fcdbe344ec8190a0471911952f4b82 completed May 7, 2026, 6:37 p.m.
Created at: April 30, 2026, 11:22 p.m.