Triple

T27992879
Position Surface form Disambiguated ID Type / Status
Subject Matteo Ricci E706927 entity
Predicate ChineseNamePinyin P41219 FINISHED
Object Lì Mǎdòu
Lì Mǎdòu is the Chinese name of Matteo Ricci, the Italian Jesuit missionary and scholar who played a pioneering role in cultural and scientific exchange between Europe and Ming-dynasty China.
E1797765 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: Lì Mǎdòu | Statement: [Matteo Ricci, ChineseNamePinyin, Lì Mǎdòu]
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: Lì Mǎdòu
Triple: [Matteo Ricci, ChineseNamePinyin, Lì Mǎdòu]
Generated description
Lì Mǎdòu is the Chinese name of Matteo Ricci, the Italian Jesuit missionary and scholar who played a pioneering role in cultural and scientific exchange between Europe and Ming-dynasty China.

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_69ef96b980d88190a753b2f9a978595a completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69f63ba8ff308190876c52b659e5979d completed May 2, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_6a13118530fc8190aad2438ae661017a completed May 24, 2026, 2:56 p.m.
NEDg Description generation batch_6a13127b3a688190b36805e60f2db695 completed May 24, 2026, 3 p.m.
NED2 Entity disambiguation (via description) batch_6a13138f4e508190b50a250487666a14 completed May 24, 2026, 3:04 p.m.
Created at: April 27, 2026, 7:51 p.m.