Triple

T13256101
Position Surface form Disambiguated ID Type / Status
Subject Shiribeshi Subprefecture E315661 entity
Predicate contains P35 FINISHED
Object Niki
Niki is a small town in Hokkaido, Japan, known for its fruit farming and rural scenery.
E1030539 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: Niki | Statement: [Shiribeshi Subprefecture, contains, Niki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Niki
Context triple: [Shiribeshi Subprefecture, contains, Niki]
  • A. Niki
    Niki is a given name that can be used for people of any gender in various cultures.
  • B. Nikki
    Nikki is a seductive and ambitious burlesque performer featured as one of the central characters in the musical film "Burlesque."
  • C. Nikki
    Nikki is the estranged wife of Pat Solitano in the film "Silver Linings Playbook," whose separation from him drives much of the movie’s emotional conflict.
  • D. Nikki
    Nikki is the central protagonist of the 1993 coming-of-age sports comedy film "Airborne," known for his laid-back California surfer attitude and exceptional inline skating skills.
  • E. Nikki
    Nikki is the commonly used first name of American politician and former U.S. Ambassador to the United Nations Nikki Haley.
  • 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: Niki
Triple: [Shiribeshi Subprefecture, contains, Niki]
Generated description
Niki is a small town in Hokkaido, Japan, known for its fruit farming and rural scenery.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Niki
Target entity description: Niki is a small town in Hokkaido, Japan, known for its fruit farming and rural scenery.
  • A. Niki
    Niki is a given name that can be used for people of any gender in various cultures.
  • B. Nikki
    Nikki is a seductive and ambitious burlesque performer featured as one of the central characters in the musical film "Burlesque."
  • C. Nikki
    Nikki is the estranged wife of Pat Solitano in the film "Silver Linings Playbook," whose separation from him drives much of the movie’s emotional conflict.
  • D. Nikki
    Nikki is the central protagonist of the 1993 coming-of-age sports comedy film "Airborne," known for his laid-back California surfer attitude and exceptional inline skating skills.
  • E. Nikki
    Nikki is the commonly used first name of American politician and former U.S. Ambassador to the United Nations Nikki Haley.
  • 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_69d806b1d9ac8190852c5571d5bd5f0f completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98f7614fc8190a1cac076d706e9aa completed April 11, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f70a4240d881909f0ee898fd272826 completed May 3, 2026, 8:41 a.m.
NEDg Description generation batch_69f70c9718d08190b09fc6723712ef55 completed May 3, 2026, 8:51 a.m.
NED2 Entity disambiguation (via description) batch_69f70d32b38881909d500b81a0164bda completed May 3, 2026, 8:54 a.m.
Created at: April 9, 2026, 9:24 p.m.