Triple

T28423854
Position Surface form Disambiguated ID Type / Status
Subject Emperor Ping of Han E720018 entity
Predicate posthumousName P744 FINISHED
Object Emperor Ping
Emperor Ping was a young Western Han dynasty ruler of China whose short reign was dominated by the regent Wang Mang, preceding the latter’s usurpation of the throne.
E1954662 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: Emperor Ping | Statement: [Emperor Ping of Han, posthumousName, Emperor Ping]
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: Emperor Ping
Triple: [Emperor Ping of Han, posthumousName, Emperor Ping]
Generated description
Emperor Ping was a young Western Han dynasty ruler of China whose short reign was dominated by the regent Wang Mang, preceding the latter’s usurpation of the throne.

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_69eff6f1c5088190bc24bfbf92f9c017 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64dfc22188190a71aa737d6320d61 completed May 2, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a296bb4f2948190a70981566595933e completed June 10, 2026, 1:50 p.m.
NEDg Description generation batch_6a296c9a1c4c81909c8fc4f25e4d0e6d completed June 10, 2026, 1:54 p.m.
NED2 Entity disambiguation (via description) batch_6a29c642277c819081131c5da71c8ce2 completed June 10, 2026, 8:17 p.m.
Created at: April 28, 2026, 1:35 a.m.