Triple

T27696646
Position Surface form Disambiguated ID Type / Status
Subject Zhu Jun E698312 entity
Predicate category P87 FINISHED
Object Eastern Han generals
Eastern Han generals were military commanders who served the Eastern Han dynasty of China, playing key roles in defending the empire and suppressing rebellions during its later, turbulent years.
E1785863 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: Eastern Han generals | Statement: [Zhu Jun, category, Eastern Han generals]
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: Eastern Han generals
Triple: [Zhu Jun, category, Eastern Han generals]
Generated description
Eastern Han generals were military commanders who served the Eastern Han dynasty of China, playing key roles in defending the empire and suppressing rebellions during its later, turbulent years.

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_69ef590ea74081908f0cd7500d85fa27 completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f6359fecc081908e1794c1905c5cc4 completed May 2, 2026, 5:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12e454d89481909ede5c9f9f35f43f completed May 24, 2026, 11:43 a.m.
NEDg Description generation batch_6a12e4fbf9cc8190b5bbff117668f81a completed May 24, 2026, 11:46 a.m.
NED2 Entity disambiguation (via description) batch_6a12e5cfee048190a139532d8e125411 completed May 24, 2026, 11:49 a.m.
Created at: April 27, 2026, 2:54 p.m.