Triple
T29689142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fung |
E751166
|
entity |
| Predicate | correspondsToPinyinSurname |
P41219
|
FINISHED |
| Object | Feng (冯) |
—
|
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: Feng (冯) | Statement: [Fung, correspondsToPinyinSurname, Feng (冯)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondsToPinyinSurname Context triple: [Fung, correspondsToPinyinSurname, Feng (冯)]
-
A.
correspondsToChineseSurname
Indicates that one entity is the Chinese surname equivalent or counterpart of another entity.
-
B.
correspondsToSurname
Indicates that one entity is the surname or family name associated with, matching, or representing the other entity.
-
C.
bearerNameInPinyin
Indicates that the bearer’s name is represented in its pinyin (romanized Chinese) form.
-
D.
spouseNameInPinyin
Indicates that it specifies the spouse’s name written in Pinyin (the Romanized form of Chinese characters).
-
E.
ChinesePinyin
chosen
Indicates that one entity is the Chinese pinyin (romanized phonetic transcription) representation of another 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_69f0d625b09481909b0b69aea1e846c8 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f6c1265c208190aacd2b551f8f0f82 |
completed | May 3, 2026, 3:29 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2415fc81908c23c311aebce66f |
completed | May 3, 2026, 3:12 a.m. |
Created at: April 28, 2026, 7:15 p.m.