Triple

T32671481
Position Surface form Disambiguated ID Type / Status
Subject Tagajō E835302 entity
Predicate hasHistoricSite P1098 FINISHED
Object Tagajō Temple ruins
Tagajō Temple ruins are the archaeological remains of an ancient Buddhist temple complex associated with the former provincial capital of Mutsu in present-day Miyagi Prefecture, Japan.
E2016896 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: Tagajō Temple ruins | Statement: [Tagajō, hasHistoricSite, Tagajō Temple ruins]
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: Tagajō Temple ruins
Triple: [Tagajō, hasHistoricSite, Tagajō Temple ruins]
Generated description
Tagajō Temple ruins are the archaeological remains of an ancient Buddhist temple complex associated with the former provincial capital of Mutsu in present-day Miyagi Prefecture, 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_69f349303ccc8190a70d0f6e8a21d3fb completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6c7ad7c5881908004680c4f7d16b0 completed May 3, 2026, 3:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3492bbba008190a75fdc19fdfbb79e completed June 19, 2026, 12:52 a.m.
NEDg Description generation batch_6a34938a58dc8190ab8e23d0b021db8b completed June 19, 2026, 12:55 a.m.
NED2 Entity disambiguation (via description) batch_6a34941dcdbc8190b6549f9be8eb672f completed June 19, 2026, 12:58 a.m.
Created at: May 1, 2026, 1:09 a.m.