Triple
T33018312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jiangjin, Sichuan, Qing Empire |
E844834
|
entity |
| Predicate | usedChineseScriptName |
P6282
|
FINISHED |
| Object | 江津縣 |
—
|
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: 江津縣 | Statement: [Jiangjin, Sichuan, Qing Empire, usedChineseScriptName, 江津縣]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedChineseScriptName Context triple: [Jiangjin, Sichuan, Qing Empire, usedChineseScriptName, 江津縣]
-
A.
usedChineseCharacters
Indicates that one entity employed or wrote using Chinese characters in relation to another entity or context.
-
B.
ChineseNameSimplified
Indicates that an entity’s name is given in simplified Chinese characters.
-
C.
ChineseNameTraditional
chosen
Indicates that an entity’s name is given in traditional Chinese characters.
-
D.
ChineseVariant
Indicates that one linguistic form is a variant of another within the Chinese language (e.g., differing by script, region, or orthographic convention).
-
E.
nameInChinese
Indicates that an entity has a specific written name or label expressed in the Chinese language.
- F. None of above.
Provenance (3 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_69f3494f3b4081909dccf2af34372a26 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d74b20a48190900dda1014cc13a8 |
completed | May 3, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69f6d26f27dc8190ae426a3e1573933e |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 1:23 a.m.