Triple

T17436585
Position Surface form Disambiguated ID Type / Status
Subject Stray Dog E424015 entity
Predicate romanizedTitle P2508 FINISHED
Object Nora inu
Nora inu is the romanized Japanese title of the 1949 Akira Kurosawa film "Stray Dog," a crime drama about a detective searching for his stolen gun in postwar Tokyo.
 E1269594 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: Nora inu | Statement: [Stray Dog, romanizedTitle, Nora inu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nora inu
Context triple: [Stray Dog, romanizedTitle, Nora inu]
  • A. Nora
    Nora is an ancient coastal settlement in southern Sardinia known as one of the island’s earliest Phoenician and later Roman archaeological sites.
  • B. Nora
    Nora is a feminine given name of Latin origin, often used independently or as a diminutive of names like Honora, Eleanor, or Leonora.
  • C. NORA
    NORA is a U.S. national research framework developed by NIOSH to guide and prioritize occupational safety and health research across key industry sectors.
  • D. Nilsa
    Nilsa is a feminine given name of Spanish origin, often used in Latin American countries.
  • E. Nina
    Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
  • 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: Nora inu
Triple: [Stray Dog, romanizedTitle, Nora inu]
Generated description
Nora inu is the romanized Japanese title of the 1949 Akira Kurosawa film "Stray Dog," a crime drama about a detective searching for his stolen gun in postwar Tokyo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nora inu
Target entity description: Nora inu is the romanized Japanese title of the 1949 Akira Kurosawa film "Stray Dog," a crime drama about a detective searching for his stolen gun in postwar Tokyo.
  • A. Nora
    Nora is a feminine given name of Latin origin, often used independently or as a diminutive of names like Honora, Eleanor, or Leonora.
  • B. Nora
    Nora is an ancient coastal settlement in southern Sardinia known as one of the island’s earliest Phoenician and later Roman archaeological sites.
  • C. NORA
    NORA is a U.S. national research framework developed by NIOSH to guide and prioritize occupational safety and health research across key industry sectors.
  • D. Nilsa
    Nilsa is a feminine given name of Spanish origin, often used in Latin American countries.
  • E. Nina
    Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
  • 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_69d889d88b6081908bada047f5b3ba51 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4490426008190b474ed76aca5d6f3 completed April 19, 2026, 3:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01aff252b88190a74781aac7c092fb completed May 11, 2026, 10:31 a.m.
NEDg Description generation batch_6a01b145221c8190b03388672af3402f completed May 11, 2026, 10:36 a.m.
NED2 Entity disambiguation (via description) batch_6a01b208e6d8819080a363da368ec2e9 completed May 11, 2026, 10:40 a.m.
Created at: April 10, 2026, 5:46 a.m.