Triple
T15663557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Won-dong |
E376627
|
entity |
| Predicate | languageUsedForAddressing |
P64298
|
FINISHED |
| Object | 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: Korean | Statement: [Won-dong, languageUsedForAddressing, Korean]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageUsedForAddressing Context triple: [Won-dong, languageUsedForAddressing, Korean]
-
A.
addressingType
Indicates the manner or form in which one entity addresses or refers to another (e.g., formally, informally, by title, or by name).
-
B.
usedInStyleOfAddress
chosen
Indicates that one entity is used as a form or style of address when referring to or speaking to another entity.
-
C.
languagePatronized
Indicates that one entity supports, promotes, or acts as a sponsor or benefactor for a particular language.
-
D.
honorificUsage
Indicates that one entity refers to or addresses another using an honorific title or respectful linguistic form.
-
E.
mediaFormOfAddress
Indicates how something is referred to or addressed within a media context (e.g., title, style, or mode of address used in media).
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f0e2668819092e52712cddd0721 |
completed | April 16, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69deda8b36a4819081cb5708fe77ef51 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:16 a.m.