Triple

T37741747
Position Surface form Disambiguated ID Type / Status
Subject Whity Umeda E940732 entity
Predicate hasSection P35 FINISHED
Object Center Mall
Center Mall is an underground shopping area that forms part of the larger Whity Umeda subterranean mall complex in Osaka, Japan.
E2245263 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: Center Mall | Statement: [Whity Umeda, hasSection, Center Mall]
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: Center Mall
Triple: [Whity Umeda, hasSection, Center Mall]
Generated description
Center Mall is an underground shopping area that forms part of the larger Whity Umeda subterranean mall complex in Osaka, Japan.

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_69f76ee0e32c8190b40a3b4cf590337c completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fbaebf2868819089b2e6ff81c572c9 completed May 6, 2026, 9:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40fb6c45d88190910f4bb96c22c90a completed June 28, 2026, 10:46 a.m.
NEDg Description generation batch_6a40fc690fe08190b4ceaadfe93be2a3 completed June 28, 2026, 10:50 a.m.
NED2 Entity disambiguation (via description) batch_6a40fce18ec08190946c064d27fcf5ad completed June 28, 2026, 10:52 a.m.
Created at: May 3, 2026, 4:18 p.m.