Triple
T28269431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jiang |
E712802
|
entity |
| Predicate | olderRomanizationSystem |
P119963
|
FINISHED |
| Object | Wade–Giles |
—
|
NE NERFINISHED |
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: Wade–Giles | Statement: [Jiang, olderRomanizationSystem, Wade–Giles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: olderRomanizationSystem Context triple: [Jiang, olderRomanizationSystem, Wade–Giles]
-
A.
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.
-
B.
formerTransliteration
Indicates that one transliteration was previously used for an entity but has since been replaced by a different transliteration.
-
C.
exampleRomanization
Indicates that one entity is a romanized representation (in Latin script) of the other entity’s original text or name.
-
D.
hasFormerRomanization
chosen
Indicates that an entity was previously written or represented using an earlier or superseded system of Romanized spelling.
-
E.
romanizationVariantOf
Indicates that one written form is a different romanized representation of the same underlying word or expression as another.
- 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_69efb5216c6881908020dce4aea65381 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f6441fa00c819092afb06beb9fb252 |
completed | May 2, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 11:17 p.m.