Triple
T7728142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ma Junren |
E175183
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ma Junren |
E175183
|
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: Ma Junren | Statement: [Ma Junren, name, Ma Junren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ma Junren Context triple: [Ma Junren, name, Ma Junren]
-
A.
Ma Junren
chosen
Ma Junren is a controversial Chinese track coach best known for training world-record-breaking female distance runners in the 1990s amid widespread doping allegations.
-
B.
He Mengxiong
He Mengxiong was a Chinese military officer and revolutionary associated with early 20th-century nationalist movements.
-
C.
Mao Xuejun
Mao Xuejun is a Chinese individual notable enough to be specifically cited as a bearer of the surname Mao, though detailed public information about their life or achievements is limited.
-
D.
Ma Zhanshan
Ma Zhanshan was a prominent Chinese general best known for his early armed resistance against the Japanese invasion of Manchuria in the 1930s.
-
E.
Mao Yuanxin
Mao Yuanxin is a Chinese political figure known as Mao Zedong’s nephew who briefly held influential positions during the final years of the Cultural Revolution.
- 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_69c6995e912c81909a49a2657103f786 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c70315e8e88190a5c7e5d2f2ef66bc |
completed | March 27, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8d6b1f7648190a0e2fd82ecb9c8b9 |
completed | March 29, 2026, 7:37 a.m. |
Created at: March 27, 2026, 4:06 p.m.