Triple

T3014270
Position Surface form Disambiguated ID Type / Status
Subject Naniwa-ku E82297 entity
Predicate hasNeighbouringWard P45005 FINISHED
Object Taisho-ku
Taisho-ku is one of Osaka City's 24 wards, known for its port facilities, industrial areas, and significant Okinawan community.
 E446502 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: Taisho-ku | Statement: [Naniwa-ku, hasNeighbouringWard, Taisho-ku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Taisho-ku
Context triple: [Naniwa-ku, hasNeighbouringWard, Taisho-ku]
  • A. Wakabayashi-ku
    Wakabayashi-ku is one of the administrative wards of Sendai, Japan, encompassing residential, commercial, and coastal areas in the eastern part of the city.
  • B. Higashi-ku
    Higashi-ku is a ward in the city of Fukuoka, Japan, known for its coastal location, residential areas, and educational institutions.
  • C. Miyagino-ku
    Miyagino-ku is one of the administrative wards of Sendai, Japan, known for its mix of residential areas, commercial facilities, and transportation hubs.
  • D. Nishi-ku
    Nishi-ku is a central ward of Yokohama, Japan, known as a major commercial and business district that includes the Minato Mirai 21 waterfront area.
  • E. Nishi-ku
    Nishi-ku is a ward in Fukuoka, Japan, known for its coastal areas, residential neighborhoods, and access to both urban amenities and natural scenery.
  • 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: Taisho-ku
Triple: [Naniwa-ku, hasNeighbouringWard, Taisho-ku]
Generated description
Taisho-ku is one of Osaka City's 24 wards, known for its port facilities, industrial areas, and significant Okinawan community.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Taisho-ku
Target entity description: Taisho-ku is one of Osaka City's 24 wards, known for its port facilities, industrial areas, and significant Okinawan community.
  • A. Wakabayashi-ku
    Wakabayashi-ku is one of the administrative wards of Sendai, Japan, encompassing residential, commercial, and coastal areas in the eastern part of the city.
  • B. Higashi-ku
    Higashi-ku is a ward in the city of Fukuoka, Japan, known for its coastal location, residential areas, and educational institutions.
  • C. Miyagino-ku
    Miyagino-ku is one of the administrative wards of Sendai, Japan, known for its mix of residential areas, commercial facilities, and transportation hubs.
  • D. Nishi-ku
    Nishi-ku is a central ward of Yokohama, Japan, known as a major commercial and business district that includes the Minato Mirai 21 waterfront area.
  • E. Nishi-ku
    Nishi-ku is a ward in Fukuoka, Japan, known for its coastal areas, residential neighborhoods, and access to both urban amenities and natural scenery.
  • 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_69ad8b1eb53481908c39bbcd1ec104b2 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9e11c4188190a3ae8fd0cbd8c2c0 completed March 8, 2026, 4:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd677fd8a481909455b2a02830bcc6 completed March 20, 2026, 3:28 p.m.
NEDg Description generation batch_69bd686cdddc819096cd8c15756803bf completed March 20, 2026, 3:31 p.m.
NED2 Entity disambiguation (via description) batch_69bd68d87d948190b5dc108b731149cb completed March 20, 2026, 3:33 p.m.
Created at: March 8, 2026, 3 p.m.