Triple

T23652017
Position Surface form Disambiguated ID Type / Status
Subject Office of the Governor-General of Korea E584191 entity
Predicate executiveBody P1001 FINISHED
Object Governor-General’s Secretariat
The Governor-General’s Secretariat was the administrative office that supported and managed the day-to-day affairs of the Japanese Governor-General overseeing colonial Korea.
E584191 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: Governor-General’s Secretariat | Statement: [Office of the Governor-General of Korea, executiveBody, Governor-General’s Secretariat]
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: Governor-General’s Secretariat
Triple: [Office of the Governor-General of Korea, executiveBody, Governor-General’s Secretariat]
Generated description
The Governor-General’s Secretariat was the administrative office that supported and managed the day-to-day affairs of the Japanese Governor-General overseeing colonial Korea.

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_69e248fefafc81909656921192f30e80 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b358ce448190a654d2cd3e81ef83 completed April 29, 2026, 7:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f45ae968081908b91cfc3d36d3f50 completed May 21, 2026, 5:49 p.m.
NEDg Description generation batch_6a0f46fb66dc8190bdbca0134bc7d00a completed May 21, 2026, 5:55 p.m.
NED2 Entity disambiguation (via description) batch_6a0f4ace63e0819081e9c2c0adf77abf completed May 21, 2026, 6:11 p.m.
Created at: April 17, 2026, 6:49 p.m.