Triple

T35342115
Position Surface form Disambiguated ID Type / Status
Subject Nakano Broadway E1020627 entity
Predicate partOf P40 FINISHED
Object Nakano shopping district
Nakano shopping district is a bustling commercial area in Tokyo known for its mix of traditional shops, eateries, and otaku culture hubs centered around the Nakano Broadway complex.
E2160235 NE FINISHED

How this triple was built (2 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: Nakano shopping district | Statement: [Nakano Broadway, partOf, Nakano shopping district]
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: Nakano shopping district
Triple: [Nakano Broadway, partOf, Nakano shopping district]
Generated description
Nakano shopping district is a bustling commercial area in Tokyo known for its mix of traditional shops, eateries, and otaku culture hubs centered around the Nakano Broadway complex.

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_69f76debb4e08190be52d89b8af2392d completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f791592c5c819097f567dde258ac26 completed May 3, 2026, 6:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38a4ccfd9c81908ce17a8553135c56 completed June 22, 2026, 2:58 a.m.
NEDg Description generation batch_6a38a59a0184819080e951c76a48eb0c completed June 22, 2026, 3:01 a.m.
NED2 Entity disambiguation (via description) batch_6a38a63caecc8190a4ac4eb8af4bb18b completed June 22, 2026, 3:04 a.m.
Created at: May 3, 2026, 4:03 p.m.