Triple
T31992141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 晏 |
E816899
|
entity |
| Predicate | readingInKoreanRevisedRomanization |
P105016
|
FINISHED |
| Object | an |
—
|
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: an | Statement: [晏, readingInKoreanRevisedRomanization, an]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: readingInKoreanRevisedRomanization Context triple: [晏, readingInKoreanRevisedRomanization, an]
-
A.
koreanReadingHangul
Indicates that an entity’s Korean reading is represented in Hangul script.
-
B.
hangulNameRomanized
chosen
Indicates that an entity’s Korean Hangul name is represented in its romanized (Latin alphabet) form.
-
C.
hasKanjiReading
Indicates that a written kanji character is associated with a specific reading or pronunciation.
-
D.
laterRomanizedInto
Indicates that an entity’s original form (such as a name, word, or title) was subsequently converted into a later Romanized (Latin-script) version.
-
E.
JapaneseNameReading
Indicates that one entity is the reading or pronunciation (e.g., in kana or romaji) of a Japanese name represented by the other entity.
- 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_69f348f8002081909a3588758ba94afb |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bbbef7a88190b0affdec1d41c1e0 |
completed | May 3, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6cef208190bc5cd43d96127004 |
completed | May 3, 2026, 3:01 a.m. |
Created at: May 1, 2026, 12:13 a.m.