Triple
T20051515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irwon-dong |
E499209
|
entity |
| Predicate | hasPrimaryLanguageUsage |
P78017
|
FINISHED |
| Object | Seoul dialect of Korean |
—
|
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: Seoul dialect of Korean | Statement: [Irwon-dong, hasPrimaryLanguageUsage, Seoul dialect of Korean]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryLanguageUsage Context triple: [Irwon-dong, hasPrimaryLanguageUsage, Seoul dialect of Korean]
-
A.
hasPrimaryLanguage1
Indicates that an entity’s main or most commonly used language is the specified language.
-
B.
hasPrimaryLanguageOfOperations
chosen
Indicates that an entity conducts its main activities or operations primarily using a specified language.
-
C.
hasPrimaryVernacularLanguageFamily
Indicates that an entity’s main vernacular language belongs to a specified language family.
-
D.
hasPrimaryLanguageBranch
Indicates that an entity’s main or dominant language belongs to a specified language branch or family.
-
E.
hasPrimaryLanguageSubbranch
Indicates that one language subbranch is the main or principal subbranch associated with a given language or language family.
- 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6632ee4d48190b9de3a1efa064492 |
completed | April 20, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69e54cee7a5c819084ae4ff26419833f |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:38 p.m.