Triple

T15446496
Position Surface form Disambiguated ID Type / Status
Subject Hatanodai E370034 entity
Predicate hasNearbyArea P4647 FINISHED
Object Nakanobu
Nakanobu is a neighborhood in Tokyo, Japan, known for its traditional shopping streets and local residential atmosphere.
 E1219074 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: Nakanobu | Statement: [Hatanodai, hasNearbyArea, Nakanobu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nakanobu
Context triple: [Hatanodai, hasNearbyArea, Nakanobu]
  • A. Kuranosuke
    Kuranosuke is the given name of Ōishi Kuranosuke, the historical leader of the Forty-seven rōnin in early 18th-century Japan.
  • B. Nobuhito
    Nobuhito, better known as Prince Takamatsu, was a Japanese imperial prince and the third son of Emperor Taishō, noted for his military career and postwar advocacy for peace.
  • C. Toshimichi
    Toshimichi is a Japanese given name most famously borne by Ōkubo Toshimichi, a key statesman and leader of the Meiji Restoration.
  • D. Tadanobu
    Tadanobu is a Japanese masculine given name most notably borne by actor and musician Tadanobu Asano.
  • E. Kenjirō
    Kenjirō is a Japanese masculine given name that can be written with various kanji combinations and is borne by multiple notable individuals in fields such as sports, arts, and entertainment.
  • 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: Nakanobu
Triple: [Hatanodai, hasNearbyArea, Nakanobu]
Generated description
Nakanobu is a neighborhood in Tokyo, Japan, known for its traditional shopping streets and local residential atmosphere.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nakanobu
Target entity description: Nakanobu is a neighborhood in Tokyo, Japan, known for its traditional shopping streets and local residential atmosphere.
  • A. Kuranosuke
    Kuranosuke is the given name of Ōishi Kuranosuke, the historical leader of the Forty-seven rōnin in early 18th-century Japan.
  • B. Nobuhito
    Nobuhito, better known as Prince Takamatsu, was a Japanese imperial prince and the third son of Emperor Taishō, noted for his military career and postwar advocacy for peace.
  • C. Toshimichi
    Toshimichi is a Japanese given name most famously borne by Ōkubo Toshimichi, a key statesman and leader of the Meiji Restoration.
  • D. Tadanobu
    Tadanobu is a Japanese masculine given name most notably borne by actor and musician Tadanobu Asano.
  • E. Kenjirō
    Kenjirō is a Japanese masculine given name that can be written with various kanji combinations and is borne by multiple notable individuals in fields such as sports, arts, and entertainment.
  • 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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ef767b4819099f2c0919a158321 completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00606823cc81908c461ef8764ebf41 completed May 10, 2026, 10:39 a.m.
NEDg Description generation batch_6a006467da5081908a7b5a8310f9d68f completed May 10, 2026, 10:56 a.m.
NED2 Entity disambiguation (via description) batch_6a0064f76df0819097d7da878e762348 completed May 10, 2026, 10:59 a.m.
Created at: April 10, 2026, 3:21 a.m.