Triple
T27992955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matteo Ricci |
E706927
|
entity |
| Predicate | usedChineseTermForGod |
P165727
|
FINISHED |
| Object | Tianzhu |
—
|
NE NERFINISHED |
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: Tianzhu | Statement: [Matteo Ricci, usedChineseTermForGod, Tianzhu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedChineseTermForGod Context triple: [Matteo Ricci, usedChineseTermForGod, Tianzhu]
-
A.
usedChineseCharacters
Indicates that one entity employed or wrote using Chinese characters in relation to another entity or context.
-
B.
hasMeaningInChinese
Indicates that one entity (such as a word, phrase, or symbol) possesses a specific meaning or interpretation within the Chinese language.
-
C.
ChineseObjective
Indicates that an entity has an objective, goal, or target specifically related to China or the Chinese context.
-
D.
ChineseAbbreviation
Indicates that one term is an abbreviation or shortened form of another term in Chinese.
-
E.
hasEthnonymInChinese
Indicates that an entity has a specific ethnonym (name for an ethnic group or people) expressed in the Chinese language.
- F. None of above. chosen
Provenance (4 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_69f65b14512c8190a40e70319dcc54cd |
completed | May 2, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f659ce58408190ba9e007b4810d4d0 |
completed | May 2, 2026, 8:08 p.m. |
| PDg | Predicate description generation | batch_69f65a6babcc81908052c9907a99c882 |
completed | May 2, 2026, 8:11 p.m. |
Created at: April 27, 2026, 7:51 p.m.