Triple
T25658896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bosudong Book Street |
E643320
|
entity |
| Predicate | typicalLanguageOfBooks |
P35318
|
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: [Bosudong Book Street, typicalLanguageOfBooks, Korean]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLanguageOfBooks Context triple: [Bosudong Book Street, typicalLanguageOfBooks, Korean]
-
A.
typicalLanguageOfReadings
Indicates the language that is most commonly used for readings or interpretations associated with a given entity.
-
B.
languageOfBooks
chosen
Indicates the language in which the referenced books are written or published.
-
C.
typicalLanguages
Indicates the languages that are commonly or characteristically used, spoken, or associated with a given entity.
-
D.
languageOfWritings
Indicates that a specified language is the one in which certain writings or written works are composed.
-
E.
languageWrittenAbout
Indicates that something is written about or concerning a particular language.
- 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_69e77e7e45648190a068ed3faa8016ea |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69fd68abf52881909c5a390c362b7c59 |
completed | May 8, 2026, 4:38 a.m. |
| PD | Predicate disambiguation | batch_69fd6812d0c88190930d8fa2d4b92490 |
completed | May 8, 2026, 4:35 a.m. |
Created at: April 21, 2026, 6:49 p.m.