Triple

T26405110
Position Surface form Disambiguated ID Type / Status
Subject Battle of Dongxing E663810 entity
Predicate commanderForCaoWei P167088 FINISHED
Object Wang Chang
Wang Chang was a military general of the Cao Wei state during China's Three Kingdoms period, noted for his role in key campaigns such as the Battle of Dongxing.
 E1757362 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: Wang Chang | Statement: [Battle of Dongxing, commanderForCaoWei, Wang Chang]
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: Wang Chang
Triple: [Battle of Dongxing, commanderForCaoWei, Wang Chang]
Generated description
Wang Chang was a military general of the Cao Wei state during China's Three Kingdoms period, noted for his role in key campaigns such as the Battle of Dongxing.

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_69ee883931888190901be96d75ee23cc completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f665a083548190ae8b9c9203dcf3b0 completed May 2, 2026, 8:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1247d654248190aea0c9bd2ff72a61 completed May 24, 2026, 12:35 a.m.
NEDg Description generation batch_6a1248bb58a48190ae84e7b538b10503 completed May 24, 2026, 12:39 a.m.
NED2 Entity disambiguation (via description) batch_6a124973e3c88190898b0cece69419b3 completed May 24, 2026, 12:42 a.m.
Created at: April 26, 2026, 11:34 p.m.