Triple
T9044729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McCune–Reischauer |
E216724
|
entity |
| Predicate | romanizesVowel |
P86055
|
FINISHED |
| Object | ㅓ as ŏ |
—
|
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: ㅓ as ŏ | Statement: [McCune–Reischauer, romanizesVowel, ㅓ as ŏ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: romanizesVowel Context triple: [McCune–Reischauer, romanizesVowel, ㅓ as ŏ]
-
A.
hasRomanizationOf
Indicates that one entity is a romanized representation (written in the Latin alphabet) of the other entity’s original script form.
-
B.
romanizationOccurred
Indicates that a process of converting text from one writing system into the Roman (Latin) alphabet has taken place.
-
C.
romanizationBegan
Indicates that the process of converting text from one writing system into its representation using the Roman (Latin) alphabet was initiated.
-
D.
hasRomanizationContrast
Indicates that there is a meaningful difference between two or more romanized representations of the same original form.
-
E.
hasRomanizationStandard
Indicates that an entity’s romanized form follows a specified romanization standard or system.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69cc5f4f1cb48190a025d1b3d8d7a790 |
completed | March 31, 2026, 11:57 p.m. |
Created at: March 30, 2026, 7:09 p.m.