Triple

T2929213
Position Surface form Disambiguated ID Type / Status
Subject Norwegian Wood (2010 film) E78918 entity
Predicate mainCharacter P1183 FINISHED
Object Midori
Midori is a central female character in Haruki Murakami’s story "Norwegian Wood," known for her lively, unconventional personality and complex relationship with the protagonist.
 E312335 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: Midori | Statement: [Norwegian Wood (2010 film), mainCharacter, Midori]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Midori
Context triple: [Norwegian Wood (2010 film), mainCharacter, Midori]
  • A. Kawaiisu
    Kawaiisu is a Native American people and their Uto-Aztecan language traditionally spoken in the southern Sierra Nevada and Tehachapi Mountains of California.
  • B. Hikifune
    Hikifune is a neighborhood in Tokyo’s Sumida ward, known as a traditional residential area with convenient access to central Tokyo.
  • C. Yukio
    Yukio is a Japanese given name commonly used for males and borne by several notable figures in politics, arts, and entertainment.
  • D. Akashi
    Akashi is a coastal city in western Japan known for its historic castle, views of the Akashi Kaikyō Strait, and its specialty dish akashiyaki.
  • E. Fujinami
    Fujinami is a Japanese surname borne by various notable individuals, including professional athletes and entertainers.
  • 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: Midori
Triple: [Norwegian Wood (2010 film), mainCharacter, Midori]
Generated description
Midori is a central female character in Haruki Murakami’s story "Norwegian Wood," known for her lively, unconventional personality and complex relationship with the protagonist.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Midori
Target entity description: Midori is a central female character in Haruki Murakami’s story "Norwegian Wood," known for her lively, unconventional personality and complex relationship with the protagonist.
  • A. Kawaiisu
    Kawaiisu is a Native American people and their Uto-Aztecan language traditionally spoken in the southern Sierra Nevada and Tehachapi Mountains of California.
  • B. Hikifune
    Hikifune is a neighborhood in Tokyo’s Sumida ward, known as a traditional residential area with convenient access to central Tokyo.
  • C. Yukio
    Yukio is a Japanese given name commonly used for males and borne by several notable figures in politics, arts, and entertainment.
  • D. Akashi
    Akashi is a coastal city in western Japan known for its historic castle, views of the Akashi Kaikyō Strait, and its specialty dish akashiyaki.
  • E. Fujinami
    Fujinami is a Japanese surname borne by various notable individuals, including professional athletes and entertainers.
  • 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_69ad8b0d40b481908bc2a5fa2e73c3fb completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad98002da4819098d6448eebcafad4 completed March 8, 2026, 3:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0866c24c88190af6c5246b5c78c70 completed March 10, 2026, 9 p.m.
NEDg Description generation batch_69b0d55128fc8190919354199e4c21bf completed March 11, 2026, 2:37 a.m.
NED2 Entity disambiguation (via description) batch_69b0d5f35adc81909af0a7cafbeb92de completed March 11, 2026, 2:39 a.m.
Created at: March 8, 2026, 2:55 p.m.