Triple
T9044723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McCune–Reischauer |
E216724
|
entity |
| Predicate | usesSpecialMarking |
P35261
|
FINISHED |
| Object | for syllable-initial ㅇ |
—
|
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: for syllable-initial ㅇ | Statement: [McCune–Reischauer, usesSpecialMarking, for syllable-initial ㅇ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesSpecialMarking Context triple: [McCune–Reischauer, usesSpecialMarking, for syllable-initial ㅇ]
-
A.
distinctiveMarking
Indicates that one entity bears a unique or distinguishing visual feature or pattern that sets it apart from others.
-
B.
mayHaveMarkings
Indicates that an entity is permitted or able to possess certain markings or distinguishing signs.
-
C.
usedMark
chosen
Indicates that one entity has employed or applied a particular mark, symbol, or indicator in some context or action.
-
D.
hasSpecial
Indicates that an entity possesses or is associated with a distinctive or exceptional attribute, status, or feature compared to others.
-
E.
hasMeasurementMarkings
Indicates that one entity bears visible measurement indicators or scale markings on its surface for quantifying something.
- 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_69ca83d22d488190adbce5e020e9cd1d |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc6b137cec8190bd1b812c10d9542a |
completed | April 1, 2026, 12:47 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee566b081909e3cdaf551dbd0ec |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:09 p.m.