Triple

T27800714
Position Surface form Disambiguated ID Type / Status
Subject Mito Castle ruins E702233 entity
Predicate hasJapaneseName P9882 FINISHED
Object 水戸城跡
水戸城跡 is the historic site of the former Mito Castle in Ibaraki Prefecture, Japan, known for its remaining earthworks, gates, and role as the seat of the Mito branch of the Tokugawa clan.
E1788849 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: 水戸城跡 | Statement: [Mito Castle ruins, hasJapaneseName, 水戸城跡]
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: 水戸城跡
Triple: [Mito Castle ruins, hasJapaneseName, 水戸城跡]
Generated description
水戸城跡 is the historic site of the former Mito Castle in Ibaraki Prefecture, Japan, known for its remaining earthworks, gates, and role as the seat of the Mito branch of the Tokugawa clan.

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_69ef8408e0588190977cffa32dc33a29 completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f6383625cc8190aa223d8ef655743c completed May 2, 2026, 5:45 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12ecd03d308190a2fd9d42bf261172 completed May 24, 2026, 12:19 p.m.
NEDg Description generation batch_6a12ed8aade48190bbec489801889492 completed May 24, 2026, 12:22 p.m.
NED2 Entity disambiguation (via description) batch_6a12ee56948881908c58657e262882a0 completed May 24, 2026, 12:25 p.m.
Created at: April 27, 2026, 5:34 p.m.