Triple

T31838322
Position Surface form Disambiguated ID Type / Status
Subject Siege of Tsingtao E812729 entity
Predicate commander P1061 FINISHED
Object Kato Sadakichi
Kato Sadakichi was an Imperial Japanese Navy admiral best known for leading Japanese naval forces during World War I, particularly in operations against German-held territories in East Asia.
E2182457 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: Kato Sadakichi | Statement: [Siege of Tsingtao, commander, Kato Sadakichi]
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: Kato Sadakichi
Triple: [Siege of Tsingtao, commander, Kato Sadakichi]
Generated description
Kato Sadakichi was an Imperial Japanese Navy admiral best known for leading Japanese naval forces during World War I, particularly in operations against German-held territories in East Asia.

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_69f348ea7ffc8190a2ab43d80277cf59 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6aff437b0819084d87a8f59be5202 completed May 3, 2026, 2:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a39b40ce980819087f4ae51f6dd47a2 completed June 22, 2026, 10:15 p.m.
NEDg Description generation batch_6a39b470cb8881908c95a74919bbcfd2 completed June 22, 2026, 10:17 p.m.
NED2 Entity disambiguation (via description) batch_6a39b52fd614819080e4b7ff905c420b completed June 22, 2026, 10:20 p.m.
Created at: April 30, 2026, 11:48 p.m.