Triple

T25008667
Position Surface form Disambiguated ID Type / Status
Subject Seibu Dome E625923 entity
Predicate locatedIn P40 FINISHED
Object Tokorozawa, Saitama Prefecture
Tokorozawa, Saitama Prefecture is a city in the Greater Tokyo area of Japan known as a residential and commercial hub and for its role in aviation history and professional baseball.
E1666430 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: Tokorozawa, Saitama Prefecture | Statement: [Seibu Dome, locatedIn, Tokorozawa, Saitama Prefecture]
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: Tokorozawa, Saitama Prefecture
Triple: [Seibu Dome, locatedIn, Tokorozawa, Saitama Prefecture]
Generated description
Tokorozawa, Saitama Prefecture is a city in the Greater Tokyo area of Japan known as a residential and commercial hub and for its role in aviation history and professional baseball.

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_69e2ff27755881908490178e83701160 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f44b13897881909482f296204b8355 completed May 1, 2026, 6:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105cdf10e081908bcd40c7e072f2e2 completed May 22, 2026, 1:40 p.m.
NEDg Description generation batch_6a105d875860819084ade4a9bf296627 completed May 22, 2026, 1:43 p.m.
NED2 Entity disambiguation (via description) batch_6a105edf54888190a3b77f63eb867749 completed May 22, 2026, 1:49 p.m.
Created at: April 18, 2026, 6:05 a.m.