Triple
T20968057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chen Long |
E516421
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | 谌龙 |
—
|
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: 谌龙 | Statement: [Chen Long, nativeName, 谌龙]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 谌龙 Context triple: [Chen Long, nativeName, 谌龙]
-
A.
Chen Long
chosen
Chen Long is a Chinese badminton player renowned for winning multiple world titles and an Olympic gold medal in men's singles.
-
B.
Ma Long
Ma Long is a Chinese table tennis player widely regarded as one of the greatest in the sport’s history, with multiple Olympic and World Championship titles.
-
C.
Lin Dan
Lin Dan is a legendary Chinese badminton player widely regarded as one of the greatest in history, known for winning multiple world and Olympic titles in men's singles.
-
D.
Wang Zhining
Wang Zhining is known primarily as the wife of Zeng Qinghong, a prominent Chinese politician and former Vice President of the People’s Republic of China.
-
E.
Yang Dong
Yang Dong is a brilliant astrophysicist from Liu Cixin’s science fiction novel *The Three-Body Problem*, known for her tragic role in uncovering the universe’s unsettling truths.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4fde6c48190af1398e7e734629e |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fb9d6b548190af7214ad2468cfbf |
completed | April 21, 2026, 4:22 a.m. |
Created at: April 16, 2026, 1:39 p.m.