Triple
T29778985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ye Xian |
E755456
|
entity |
| Predicate | earliestTextualSourceLanguage |
P3926
|
FINISHED |
| Object | Classical Chinese |
—
|
LITERAL 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: Classical Chinese | Statement: [Ye Xian, earliestTextualSourceLanguage, Classical Chinese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: earliestTextualSourceLanguage Context triple: [Ye Xian, earliestTextualSourceLanguage, Classical Chinese]
-
A.
languageOfEarliestForm
chosen
Indicates the language in which the earliest known form or attested version of something (e.g., a text, name, or expression) is recorded.
-
B.
originalTextLanguage
Indicates the language in which a text was originally written or created before any translation or adaptation.
-
C.
earliestTextsIn
Indicates that certain texts are among the earliest known examples found in or associated with a particular place or context.
-
D.
languageOfSources
Indicates that the specified language is the language in which the referenced sources or source materials are expressed.
-
E.
languageOfManuscript
Indicates the language in which a given manuscript is written.
- 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_69f0ef878574819088c867fd1a5c8b86 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc53f4f881908dcc698687bbb64d |
completed | May 3, 2026, 7:42 a.m. |
Created at: April 28, 2026, 8:48 p.m.