Triple

T7766002
Position Surface form Disambiguated ID Type / Status
Subject Rheinbach E176146 entity
Predicate hasTwinTown P919 FINISHED
Object Miyakonojō
Miyakonojō is a city in Miyazaki Prefecture on Japan’s Kyushu island, known for its agriculture and livestock production.
 E935447 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: Miyakonojō | Statement: [Rheinbach, hasTwinTown, Miyakonojō]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Miyakonojō
Context triple: [Rheinbach, hasTwinTown, Miyakonojō]
  • A. Kamishihoro
    Kamishihoro is a town in Hokkaido, Japan, known for its natural scenery, hot springs, and the historic Taushubetsu River Bridge within the Daisetsuzan mountain region.
  • B. Kameyama
    Kameyama is a city in Mie Prefecture, Japan, known historically as a post town on the Tōkaidō and for its preserved castle ruins and traditional streetscapes.
  • C. Tokushima
    Tokushima is a coastal city on Japan’s Shikoku Island known for its annual Awa Odori dance festival and role as a regional cultural and economic center.
  • D. Toyokawa
    Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
  • E. Ichinomiya
    Ichinomiya is a city in Aichi Prefecture, Japan, known historically as a textile and commercial center within the Nagoya metropolitan area.
  • 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: Miyakonojō
Triple: [Rheinbach, hasTwinTown, Miyakonojō]
Generated description
Miyakonojō is a city in Miyazaki Prefecture on Japan’s Kyushu island, known for its agriculture and livestock production.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Miyakonojō
Target entity description: Miyakonojō is a city in Miyazaki Prefecture on Japan’s Kyushu island, known for its agriculture and livestock production.
  • A. Kamishihoro
    Kamishihoro is a town in Hokkaido, Japan, known for its natural scenery, hot springs, and the historic Taushubetsu River Bridge within the Daisetsuzan mountain region.
  • B. Kameyama
    Kameyama is a city in Mie Prefecture, Japan, known historically as a post town on the Tōkaidō and for its preserved castle ruins and traditional streetscapes.
  • C. Tokushima
    Tokushima is a coastal city on Japan’s Shikoku Island known for its annual Awa Odori dance festival and role as a regional cultural and economic center.
  • D. Toyokawa
    Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
  • E. Ichinomiya
    Ichinomiya is a city in Aichi Prefecture, Japan, known historically as a textile and commercial center within the Nagoya metropolitan area.
  • 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_69c69962923c8190ac74d28b4f9fe0a0 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7043279748190b30882e9cc6cca54 completed March 27, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69e712b2ff1081908ccf311e1133ab72 completed April 21, 2026, 6:01 a.m.
NEDg Description generation batch_69e720f4015c81909ba7973c3e781985 completed April 21, 2026, 7:02 a.m.
NED2 Entity disambiguation (via description) batch_69e75a7a04c88190bb8f3dd3f3e435ef completed April 21, 2026, 11:07 a.m.
Created at: March 27, 2026, 4:09 p.m.