Triple

T19754917
Position Surface form Disambiguated ID Type / Status
Subject Snow Crash E474477 entity
Predicate mainCharacter P1183 FINISHED
Object Raven
Raven is a formidable and enigmatic Aleutian harpooner and antagonist in Neal Stephenson’s cyberpunk novel "Snow Crash," known for his lethal skills and deep-seated vendetta against the United States.
E1394755 NE FINISHED

How this triple was built (4 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: Raven | Statement: [Snow Crash, mainCharacter, Raven]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Raven
Context triple: [Snow Crash, mainCharacter, Raven]
  • A. Raven
    Raven is a central trickster-creator figure in Haida mythology, known for shaping the world and bringing light and knowledge to humanity.
  • B. Raven
    Raven is a minor character appearing in the "Genesis of the Daleks" serial from the long-running British science fiction television series Doctor Who.
  • C. Raven
    Raven is the mascot representing Sequoia High School’s athletic teams and school spirit.
  • D. Raven
    Raven is a fictional character who appears in the comic series "Old Wounds," serving as a key figure in its narrative.
  • E. Raven
    Raven is a component or section within the work "The Art of Doing Nothing," likely contributing a distinct thematic or narrative element to the overall piece.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Raven
Triple: [Snow Crash, mainCharacter, Raven]
Generated description
Raven is a formidable and enigmatic Aleutian harpooner and antagonist in Neal Stephenson’s cyberpunk novel "Snow Crash," known for his lethal skills and deep-seated vendetta against the United States.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Raven
Target entity description: Raven is a formidable and enigmatic Aleutian harpooner and antagonist in Neal Stephenson’s cyberpunk novel "Snow Crash," known for his lethal skills and deep-seated vendetta against the United States.
  • A. Raven
    Raven is a powerful, empathic half-demon sorceress and core member of the Teen Titans, known for her dark, reserved personality and struggle to control her immense magical abilities.
  • B. Raven
    Raven is the blue-skinned, shape-shifting mutant better known as Mystique in Marvel's X-Men universe.
  • C. Raven
    Raven is a central trickster-creator figure in Haida mythology, known for shaping the world and bringing light and knowledge to humanity.
  • D. Raven
    Raven is the central protagonist of "Apprentice Part 1," around whom the story’s main events and character development revolve.
  • E. Raven
    Raven is a fictional character who appears in the comic series "Old Wounds," serving as a key figure in its narrative.
  • F. None of above. chosen

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_69d8e51940a0819087bd2996f98da668 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6529dada081909c5b4d65247c6032 completed April 20, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a07bd67064081908839a408b0e746e1 completed May 16, 2026, 12:42 a.m.
NEDg Description generation batch_6a07bde28e848190aaa9c4a06b31bdb6 completed May 16, 2026, 12:44 a.m.
NED2 Entity disambiguation (via description) batch_6a07bed4c8d8819094fafce7eee69ee7 completed May 16, 2026, 12:48 a.m.
Created at: April 10, 2026, 1:48 p.m.