Triple

T30481148
Position Surface form Disambiguated ID Type / Status
Subject Guo Zongxun E775589 entity
Predicate mother P120 FINISHED
Object Empress Fu the Elder
Empress Fu the Elder was a Song dynasty empress of China best known as the mother of Emperor Guo Zongxun and a prominent figure in the final years of the Later Zhou dynasty.
 E2156257 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 Fu the Elder | Statement: [Guo Zongxun, mother, Empress Fu the Elder]
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 Fu the Elder
Triple: [Guo Zongxun, mother, Empress Fu the Elder]
Generated description
Empress Fu the Elder was a Song dynasty empress of China best known as the mother of Emperor Guo Zongxun and a prominent figure in the final years of the Later Zhou dynasty.

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_69f22497341481909c21ba329fadaa6b completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f687415610819081818d08f7c79a81 completed May 2, 2026, 11:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3891419b808190a3b951ab1bda560f completed June 22, 2026, 1:34 a.m.
NEDg Description generation batch_6a389278e6948190998204bd8d7bf1bc completed June 22, 2026, 1:40 a.m.
NED2 Entity disambiguation (via description) batch_6a38930372408190a387347aba837518 completed June 22, 2026, 1:42 a.m.
Created at: April 29, 2026, 8:12 p.m.