Triple
T13872728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wu Dajing |
E333494
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Wu Dajing |
E333494
|
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: Wu Dajing | Statement: [Wu Dajing, name, Wu Dajing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wu Dajing Context triple: [Wu Dajing, name, Wu Dajing]
-
A.
Wu Dajing
chosen
Wu Dajing is a Chinese short track speed skater and Olympic champion known for his world-record performances in the 500-meter event.
-
B.
Wu Minxia
Wu Minxia is a Chinese diver and multiple Olympic gold medalist renowned for her dominance in synchronized and springboard diving events.
-
C.
Yang Jinyu
Yang Jinyu was a Chinese military figure and graduate of the Yunnan Military Academy who became notable for his role in early 20th-century Chinese military and political affairs.
-
D.
Liu Wei
Liu Wei is a prominent Chinese basketball player and longtime point guard for the Shanghai Sharks who also represented China in multiple international competitions, including the Olympics.
-
E.
Chen Lu
Chen Lu is a Chinese figure skater renowned as one of the sport’s early stars from China, celebrated for her artistic style and historic World and Olympic medals in the 1990s.
- 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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de05c638248190bbe5d19f7b88d0f9 |
completed | April 14, 2026, 9:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c107c20c81909dff0ca4a59fcc55 |
completed | May 3, 2026, 9:41 p.m. |
Created at: April 9, 2026, 10:14 p.m.