Triple

T30343278
Position Surface form Disambiguated ID Type / Status
Subject Working!! E771810 entity
Predicate fictionalRestaurantName P9480 FINISHED
Object Wagnaria
Wagnaria is the quirky family restaurant setting of the comedy anime and manga series "Working!!", where an eccentric staff drives much of the series’ humor and slice-of-life storytelling.
 E1909438 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: Wagnaria | Statement: [Working!!, fictionalRestaurantName, Wagnaria]
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: Wagnaria
Triple: [Working!!, fictionalRestaurantName, Wagnaria]
Generated description
Wagnaria is the quirky family restaurant setting of the comedy anime and manga series "Working!!", where an eccentric staff drives much of the series’ humor and slice-of-life storytelling.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: fictionalRestaurantName
Context triple: [Working!!, fictionalRestaurantName, Wagnaria]
  • A. hasFictionalDiner
    Indicates that one entity features or includes a fictional diner associated with another entity.
  • B. restaurantName chosen
    Indicates the name assigned to a restaurant as its identifying label.
  • C. fictionalRanchName
    Indicates that an entity is associated with a name used for a fictional ranch.
  • D. fictionalOrganizationName
    Indicates that the relationship specifies the name assigned to a fictional organization.
  • E. fictionalSanctuaryName
    Indicates that an entity has a designated name used for a fictional sanctuary or refuge.
  • 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_69f2248b9a208190bc3e6804acd5afd6 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69fd0d0ba5c48190bddb3f0e6637544c completed May 7, 2026, 10:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a277c2559148190a49afbd63f7a3273 completed June 9, 2026, 2:36 a.m.
NEDg Description generation batch_6a277cd679cc8190884aee72afff3e23 completed June 9, 2026, 2:39 a.m.
NED2 Entity disambiguation (via description) batch_6a277d8c04c481909264027d62855ed9 completed June 9, 2026, 2:42 a.m.
PD Predicate disambiguation batch_69fd0c4324a8819086c90adf46216e0e completed May 7, 2026, 10:03 p.m.
Created at: April 29, 2026, 7:55 p.m.