Triple

T24090528
Position Surface form Disambiguated ID Type / Status
Subject 内閣法制局長官 E596774 entity
Predicate legalBasis P125 FINISHED
Object 内閣法制局設置法
内閣法制局設置法は、日本の内閣法制局の組織や権限、長官の地位などを定める日本の法律である。
E26650 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: 内閣法制局設置法 | Statement: [内閣法制局長官, legalBasis, 内閣法制局設置法]
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: 内閣法制局設置法
Triple: [内閣法制局長官, legalBasis, 内閣法制局設置法]
Generated description
内閣法制局設置法は、日本の内閣法制局の組織や権限、長官の地位などを定める日本の法律である。

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_69e288c4638c81909bacc28a1e3d436b completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1dc2e672c8190b3e4be041835cc27 completed April 29, 2026, 10:23 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f9678a45881909271655316c0e5d7 completed May 21, 2026, 11:34 p.m.
NEDg Description generation batch_6a0f973823ac819092f241755fe86bf2 completed May 21, 2026, 11:37 p.m.
NED2 Entity disambiguation (via description) batch_6a0f98194640819086e65f85bb0bede1 completed May 21, 2026, 11:41 p.m.
Created at: April 17, 2026, 10:52 p.m.