Triple
T16509442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luo Ping |
E401018
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Luo Ping |
E401018
|
NE 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: Luo Ping | Statement: [Luo Ping, name, Luo Ping]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luo Ping Context triple: [Luo Ping, name, Luo Ping]
-
A.
Luo Ping
chosen
Luo Ping was an 18th-century Chinese painter of the Qing dynasty, renowned for his imaginative and eerie ghost-themed works and association with the Yangzhou school.
-
B.
Luo Feng-ping
Luo Feng-ping is a Taiwanese public figure who served as First Lady of the Republic of China, accompanying and supporting the presidency through official and ceremonial duties.
-
C.
Luo Peijin
Luo Peijin was a Chinese military officer and notable graduate of the Yunnan Military Academy who played a role in early 20th-century Chinese military and political affairs.
-
D.
Liu Ping
Liu Ping is a Chinese individual best known as a child of former President of the People's Republic of China and prominent Communist leader Liu Shaoqi.
-
E.
Peng Xiaolian
Peng Xiaolian was a prominent Chinese film director and screenwriter known for her nuanced portrayals of women's lives and Shanghai's urban culture.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d88381f6148190819958a038be990e |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e54f7508190804bbae4c9bc8fe3 |
completed | April 18, 2026, 7:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00758bc924819099f29d01bd8a02a0 |
completed | May 10, 2026, 12:09 p.m. |
Created at: April 10, 2026, 5:14 a.m.