Triple

T34589010
Position Surface form Disambiguated ID Type / Status
Subject Marjorie Liu E888123 entity
Predicate hasWrittenShortFiction P78982 FINISHED
Object Hunter Kiss stories
Hunter Kiss stories are a series of urban fantasy tales by Marjorie Liu featuring a demon-hunting heroine bound to a group of living tattoos that come alive at night.
 E2101888 NE FINISHED

How this triple was built (3 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: Hunter Kiss stories | Statement: [Marjorie Liu, hasWrittenShortFiction, Hunter Kiss stories]
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: Hunter Kiss stories
Triple: [Marjorie Liu, hasWrittenShortFiction, Hunter Kiss stories]
Generated description
Hunter Kiss stories are a series of urban fantasy tales by Marjorie Liu featuring a demon-hunting heroine bound to a group of living tattoos that come alive at night.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasWrittenShortFiction
Context triple: [Marjorie Liu, hasWrittenShortFiction, Hunter Kiss stories]
  • A. hasWrittenFiction chosen
    Indicates that one entity is the creator or author of fictional written works associated with another entity.
  • B. hasWrittenNonFiction
    Indicates that a person is the author of one or more non-fiction works.
  • C. hasFictionComponent
    Indicates that something includes, contains, or is composed in part of a fictional element or work.
  • D. hasAssociatedWorkOfFiction
    Indicates that an entity is linked to a related work of fiction, such as a novel, film, or story that is associated with it.
  • E. hasWrittenAbout
    Indicates that one entity has authored content or material discussing, analyzing, or referencing another entity.
  • F. None of above.

Provenance (6 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_69f349d3bfcc81909874c99e646fb3ea completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f7234bcaa48190ac970759d34e254a completed May 3, 2026, 10:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37363f21a48190a7d371f4a50d27f7 completed June 21, 2026, 12:54 a.m.
NEDg Description generation batch_6a37373c8d2c8190b29f4a91836b6e40 completed June 21, 2026, 12:58 a.m.
NED2 Entity disambiguation (via description) batch_6a3737bde2e8819099605cf04b5de6f1 completed June 21, 2026, 1 a.m.
PD Predicate disambiguation batch_69f72155c48881909bd40b9aa3febd5a completed May 3, 2026, 10:20 a.m.
Created at: May 1, 2026, 2:03 a.m.