Triple

T26740627
Position Surface form Disambiguated ID Type / Status
Subject Fukushima Masanori E674241 entity
Predicate courtTitle P23246 FINISHED
Object Higo no Kami
Higo no Kami was a prestigious Japanese court title historically granted to high-ranking samurai and officials, often associated with governance or honorary authority over Higo Province.
E1738607 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: Higo no Kami | Statement: [Fukushima Masanori, courtTitle, Higo no Kami]
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: Higo no Kami
Triple: [Fukushima Masanori, courtTitle, Higo no Kami]
Generated description
Higo no Kami was a prestigious Japanese court title historically granted to high-ranking samurai and officials, often associated with governance or honorary authority over Higo Province.

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_69eecda63a3881908095c47900692e65 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f6187e939c81908e5da8b43227a444 completed May 2, 2026, 3:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11fe9f3eb88190a5c99b42ff85ced0 completed May 23, 2026, 7:23 p.m.
NEDg Description generation batch_6a11ff67f7748190ad1c6874be3660e1 completed May 23, 2026, 7:26 p.m.
NED2 Entity disambiguation (via description) batch_6a11fffd6b1081909ed36e05ffdaed73 completed May 23, 2026, 7:29 p.m.
Created at: April 27, 2026, 3:49 a.m.