Triple
T16471948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mao Na |
E400083
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Mao Na |
E400083
|
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: Mao Na | Statement: [Mao Na, name, Mao Na]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mao Na Context triple: [Mao Na, name, Mao Na]
-
A.
Mao Na
chosen
Mao Na is the birth name of Chinese tennis champion Li Na, the first Asian player to win a Grand Slam singles title.
-
B.
Mao Ning
Mao Ning is a Chinese diplomat and politician who has served as the spokesperson for China’s Ministry of Foreign Affairs.
-
C.
Mao Xinyu
Mao Xinyu is a Chinese major general and military historian best known as the grandson of Mao Zedong.
-
D.
Mao Xueying
Mao Xueying is a Chinese individual notable for bearing the surname Mao, though specific widely recognized public achievements or roles are not well documented.
-
E.
Wang Miao
Wang Miao is a central protagonist in Liu Cixin’s Remembrance of Earth’s Past trilogy, a nanomaterials researcher whose investigation into a series of strange phenomena draws him into humanity’s first contact with an alien civilization.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32dd19df881909e4562a5e8473338 |
completed | April 18, 2026, 7:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f5d16008190bd874080e86b8a2f |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 5:11 a.m.