Triple

T32448313
Position Surface form Disambiguated ID Type / Status
Subject Zhao Gao E829205 entity
Predicate associatedWith P37 FINISHED
Object Fusu
Fusu was the eldest son and designated heir of Qin Shi Huang, whose forced suicide amid court intrigue helped trigger the collapse of the Qin dynasty.
E2007813 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: Fusu | Statement: [Zhao Gao, associatedWith, Fusu]
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: Fusu
Triple: [Zhao Gao, associatedWith, Fusu]
Generated description
Fusu was the eldest son and designated heir of Qin Shi Huang, whose forced suicide amid court intrigue helped trigger the collapse of the Qin 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_69f3491d2e5c819092b1c9535beff8ec completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c2e822a88190a7b32d03127a2025 completed May 3, 2026, 3:37 a.m.
NED1 Entity disambiguation (via context triple) batch_6a346678b660819082bf871b00b4fb26 completed June 18, 2026, 9:43 p.m.
NEDg Description generation batch_6a34674302f081908ce094e58ee8360c completed June 18, 2026, 9:46 p.m.
NED2 Entity disambiguation (via description) batch_6a3468279dbc8190b5efcecd6f4aa23c completed June 18, 2026, 9:50 p.m.
Created at: May 1, 2026, 12:56 a.m.