Triple
T29688956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 胡 |
E751161
|
entity |
| Predicate | surnameRomanization |
P168010
|
FINISHED |
| Object | Hu |
—
|
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: Hu | Statement: [胡, surnameRomanization, Hu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: surnameRomanization Context triple: [胡, surnameRomanization, Hu]
-
A.
nameInLanguageRomanization
Indicates that an entity’s name is represented in the romanized (Latin-script) form of a particular language.
-
B.
exampleRomanization
Indicates that one entity is a romanized representation (in Latin script) of the other entity’s original text or name.
-
C.
nameInMcCuneReischauer
Indicates that an entity’s name is represented using the McCune–Reischauer romanization system.
-
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.
hasRomanizationOf
Indicates that one entity is a romanized representation (written in the Latin alphabet) of the other entity’s original script form.
- 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_69f0d625b09481909b0b69aea1e846c8 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f67292c75c8190a09ab2fb88fc1a33 |
completed | May 2, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69f66abfdaf08190a55f14c70be6fd4d |
completed | May 2, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69f66d75a8788190aa9ca2c977429045 |
completed | May 2, 2026, 9:32 p.m. |
Created at: April 28, 2026, 7:15 p.m.