Triple

T30760404
Position Surface form Disambiguated ID Type / Status
Subject Emperor He of Han E783217 entity
Predicate spouse P13 FINISHED
Object Empress Deng Sui
Empress Deng Sui was a powerful and respected Eastern Han dynasty empress and regent known for her capable governance, promotion of Confucian values, and efforts to stabilize the empire during her rule.
E2175770 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: Empress Deng Sui | Statement: [Emperor He of Han, spouse, Empress Deng Sui]
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: Empress Deng Sui
Triple: [Emperor He of Han, spouse, Empress Deng Sui]
Generated description
Empress Deng Sui was a powerful and respected Eastern Han dynasty empress and regent known for her capable governance, promotion of Confucian values, and efforts to stabilize the empire during her rule.

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_69f224b047f48190b4f5efeb7ee97b37 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68f9b56988190a95f2706bb6b3217 completed May 2, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a394d119dc481908fde7eb04ecc514e completed June 22, 2026, 2:56 p.m.
NEDg Description generation batch_6a394e193f4c81908694652d7126698d completed June 22, 2026, 3 p.m.
NED2 Entity disambiguation (via description) batch_6a3968453570819084081dc21fc59a21 completed June 22, 2026, 4:52 p.m.
Created at: April 29, 2026, 8:39 p.m.