Triple
T34242843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Longhui County |
E878511
|
entity |
| Predicate | languageVarietyRegionOf |
P202179
|
FINISHED |
| Object | Old Xiang |
—
|
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: Old Xiang | Statement: [Longhui County, languageVarietyRegionOf, Old Xiang]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageVarietyRegionOf Context triple: [Longhui County, languageVarietyRegionOf, Old Xiang]
-
A.
languageFamilyRegion
Indicates the geographic region or area in which a language family is predominantly found or historically associated.
-
B.
linguisticVariant
Indicates that one linguistic form is an alternative version or expression of another within the same or closely related language context.
-
C.
regionLanguage
Indicates that a particular language is used or officially recognized within a specific geographic region.
-
D.
regionOfMajorLanguage
Indicates the geographic region where a particular language is predominantly spoken or holds major usage.
-
E.
denotesLanguageVariety
Indicates that one entity specifies the particular variety, dialect, or form of language used or associated with another entity.
- 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_69f349b3618481909df955b063f305b2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a005d878aec81908e1177914a8fb610 |
completed | May 10, 2026, 10:27 a.m. |
| PD | Predicate disambiguation | batch_6a005c382f8881908ff33ebb7f88c430 |
completed | May 10, 2026, 10:21 a.m. |
| PDg | Predicate description generation | batch_6a005d86d6e481909e9f6ae81568cfb8 |
completed | May 10, 2026, 10:27 a.m. |
Created at: May 1, 2026, 1:56 a.m.