Triple

T11749637
Position Surface form Disambiguated ID Type / Status
Subject Ikebana E279371 entity
Predicate hasStyle P1609 FINISHED
Object rikka
Rikka is a classical, highly formal style of Japanese ikebana characterized by upright, elaborate arrangements that symbolically represent natural landscapes.
E944842 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: rikka | Statement: [Ikebana, hasStyle, rikka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: rikka
Context triple: [Ikebana, hasStyle, rikka]
  • A. Kirakira
    Kirakira is a small coastal town in the Solomon Islands that serves as the administrative and commercial center of Makira-Ulawa Province.
  • B. Rie
    Rie is a common diminutive or nickname form of the given name Marie, used in various European languages.
  • C. Rina
    Rina is a feminine given name commonly used as a short or diminutive form of longer names such as Caterina.
  • D. Riri
    Riri is a diminutive form of the given name Henri, often used as an affectionate nickname.
  • E. Katikkiro
    Katikkiro is the traditional title for the prime minister and chief administrative officer of the Kingdom of Buganda in Uganda.
  • 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: rikka
Triple: [Ikebana, hasStyle, rikka]
Generated description
Rikka is a classical, highly formal style of Japanese ikebana characterized by upright, elaborate arrangements that symbolically represent natural landscapes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: rikka
Target entity description: Rikka is a classical, highly formal style of Japanese ikebana characterized by upright, elaborate arrangements that symbolically represent natural landscapes.
  • A. Kirakira
    Kirakira is a small coastal town in the Solomon Islands that serves as the administrative and commercial center of Makira-Ulawa Province.
  • B. Rie
    Rie is a common diminutive or nickname form of the given name Marie, used in various European languages.
  • C. Rina
    Rina is a feminine given name commonly used as a short or diminutive form of longer names such as Caterina.
  • D. Riri
    Riri is a diminutive form of the given name Henri, often used as an affectionate nickname.
  • E. Katikkiro
    Katikkiro is the traditional title for the prime minister and chief administrative officer of the Kingdom of Buganda in Uganda.
  • 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_69d6ab01038c819080714901502c84fc completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a508b0c4819082fbcc27d559ea2f completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f01a0492b48190b6f2e3cf36b4f537 completed April 28, 2026, 2:23 a.m.
NEDg Description generation batch_69f0319520dc8190817c5e75ddb7d40b completed April 28, 2026, 4:03 a.m.
NED2 Entity disambiguation (via description) batch_69f05ad36e4c8190b7239e5b33713369 completed April 28, 2026, 6:59 a.m.
Created at: April 8, 2026, 9:41 p.m.