Triple
T1334774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pusan National University |
E28722
|
entity |
| Predicate | nativeNameLang |
P15
|
FINISHED |
| Object | ko |
—
|
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: ko | Statement: [Pusan National University, nativeNameLang, ko]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nativeNameLang Context triple: [Pusan National University, nativeNameLang, ko]
-
A.
nativeLanguage
Indicates the language that a person or entity originally learned and uses as their primary or first language.
-
B.
traditionalLanguageName
Indicates the name traditionally used in a particular language to refer to the subject entity.
-
C.
languageOfWorkOrName
chosen
Indicates the language in which a work is created or a name is expressed.
-
D.
standardLanguageOf
Indicates that one entity serves as the officially recognized or commonly used standard language for another entity (such as a country, region, or organization).
-
E.
macrolanguageOf
Indicates that one language functions as a macrolanguage encompassing or grouping together one or more related individual languages.
- 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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1eb119881909dd5fbf728d9e8ba |
completed | March 1, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69a4bef174708190a07bbc697fe19a2d |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.