Triple
T7724247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ma Long |
E175088
|
entity |
| Predicate | AsianChampionshipsTitle |
P50371
|
FINISHED |
| Object | multiple men's singles titles |
—
|
LITERAL 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: multiple men's singles titles | Statement: [Ma Long, AsianChampionshipsTitle, multiple men's singles titles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: AsianChampionshipsTitle Context triple: [Ma Long, AsianChampionshipsTitle, multiple men's singles titles]
-
A.
AsianChampionshipTitles
chosen
Indicates the number of championship titles an entity has won in Asian-level competitions or tournaments.
-
B.
asiaCupWinner
Indicates that one entity is the champion or winning team of the Asia Cup tournament in a given edition or year.
-
C.
wonAsianCupWinnersCup
Indicates that one entity (typically a sports team or club) has won the Asian Cup Winners' Cup competition.
-
D.
afconTitles
Indicates the number of Africa Cup of Nations (AFCON) championship titles an entity has won.
-
E.
AsianGamesGoldMedals
Indicates that the subject has won one or more gold medals at the Asian Games.
- F. None of above.
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_69c6995d541c81909eaa646b1a8369a9 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7074eca4c8190bd51fd1b450729e8 |
completed | March 27, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69c7016a6cf88190b53bf4b958f0f302 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:05 p.m.