Triple

T28459552
Position Surface form Disambiguated ID Type / Status
Subject Sun Quan E720111 entity
Predicate sibling P363 FINISHED
Object Sun Shangxiang
Sun Shangxiang was a noblewoman of the Eastern Wu state during the late Eastern Han dynasty, historically noted as Sun Quan’s sister and the politically significant wife of the warlord Liu Bei.
E1822665 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: Sun Shangxiang | Statement: [Sun Quan, sibling, Sun Shangxiang]
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: Sun Shangxiang
Triple: [Sun Quan, sibling, Sun Shangxiang]
Generated description
Sun Shangxiang was a noblewoman of the Eastern Wu state during the late Eastern Han dynasty, historically noted as Sun Quan’s sister and the politically significant wife of the warlord Liu Bei.

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_69f01a58a67c819097936d9e8da8d6e6 completed April 28, 2026, 2:24 a.m.
NER Named-entity recognition batch_69f64ea3ff048190b6e0ca0fd79c8f30 completed May 2, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cac3f75948190b06461ba1fe4894f completed May 31, 2026, 9:46 p.m.
NEDg Description generation batch_6a1cacfc26bc8190ad65e3f8ef7d6d7b completed May 31, 2026, 9:49 p.m.
NED2 Entity disambiguation (via description) batch_6a1cadfb2d808190b2b46e8e2b7e2274 completed May 31, 2026, 9:54 p.m.
Created at: April 28, 2026, 2:38 a.m.