Triple

T16236463
Position Surface form Disambiguated ID Type / Status
Subject Aizu Domain E394124 entity
Predicate successorEntity P3901 FINISHED
Object Wakamatsu Prefecture
Wakamatsu Prefecture was a short-lived Meiji-era administrative division in Japan that replaced the former Aizu Domain before later being merged into Fukushima Prefecture.
E2291036 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: Wakamatsu Prefecture | Statement: [Aizu Domain, successorEntity, Wakamatsu 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: Wakamatsu Prefecture
Triple: [Aizu Domain, successorEntity, Wakamatsu Prefecture]
Generated description
Wakamatsu Prefecture was a short-lived Meiji-era administrative division in Japan that replaced the former Aizu Domain before later being merged into Fukushima Prefecture.

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_69d87f204df88190a8f88923decf9835 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2455abc608190ba3308c15c9e8a23 completed April 17, 2026, 2:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5c1e9f9cb881909f7db9cd380aa001 completed July 19, 2026, 12:47 a.m.
NEDg Description generation batch_6a5c1f17a73c8190a8a90cd17f29df6c completed July 19, 2026, 12:49 a.m.
NED2 Entity disambiguation (via description) batch_6a5c1ffdadc08190b9f67c4ce2d1b728 completed July 19, 2026, 12:53 a.m.
Created at: April 10, 2026, 5:04 a.m.