Triple

T18613756
Position Surface form Disambiguated ID Type / Status
Subject Shinagawa Station area E454964 entity
Predicate containsShoppingFacility P37662 FINISHED
Object ウィング高輪
ウィング高輪は、品川駅近くに位置し、ファッションや飲食店などが集まるショッピング施設です。
 E1334069 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: ウィング高輪 | Statement: [Shinagawa Station area, containsShoppingFacility, ウィング高輪]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ウィング高輪
Context triple: [Shinagawa Station area, containsShoppingFacility, ウィング高輪]
  • A. Wing
    Wing is an experimental mobile operating system and user interface project developed by X (formerly Google X) to explore new paradigms in smartphone interaction and design.
  • B. Wing
    Wing is an Alphabet Inc. subsidiary focused on developing and operating drone-based delivery services and related logistics technologies.
  • C. Wing
    Wing is a Japanese lingerie and intimate apparel brand known for its comfortable, everyday undergarments for women.
  • D. Wing
    Wing is a record label imprint associated with the release of the song "Feels Good."
  • E. New Wing
    New Wing is a later Baroque extension of Berlin’s Charlottenburg Palace, known for its richly decorated state apartments and royal ceremonial rooms.
  • 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: ウィング高輪
Triple: [Shinagawa Station area, containsShoppingFacility, ウィング高輪]
Generated description
ウィング高輪は、品川駅近くに位置し、ファッションや飲食店などが集まるショッピング施設です。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ウィング高輪
Target entity description: ウィング高輪は、品川駅近くに位置し、ファッションや飲食店などが集まるショッピング施設です。
  • A. Wing
    Wing is an experimental mobile operating system and user interface project developed by X (formerly Google X) to explore new paradigms in smartphone interaction and design.
  • B. Wing
    Wing is an Alphabet Inc. subsidiary focused on developing and operating drone-based delivery services and related logistics technologies.
  • C. Wing
    Wing is a Japanese lingerie and intimate apparel brand known for its comfortable, everyday undergarments for women.
  • D. Wing
    Wing is a record label imprint associated with the release of the song "Feels Good."
  • E. New Wing
    New Wing is a later Baroque extension of Berlin’s Charlottenburg Palace, known for its richly decorated state apartments and royal ceremonial rooms.
  • 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_69d8d38bbe7c8190bdec3138e7d413c9 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e54d03feb88190bbd8889273d82f7f completed April 19, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_6a05038c4d408190acb54ceaeaf470c5 completed May 13, 2026, 11:04 p.m.
NEDg Description generation batch_6a05065fcdd8819083644c9bceb556c9 completed May 13, 2026, 11:16 p.m.
NED2 Entity disambiguation (via description) batch_6a0506f2ff9c81909995a299641c6c37 completed May 13, 2026, 11:19 p.m.
Created at: April 10, 2026, 11:45 a.m.