Triple
T15972217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maurice Greene |
E387351
|
entity |
| Predicate | IAAFWorldCupGoldMedal |
P120673
|
FINISHED |
| Object | 1998 Johannesburg – men’s 100 metres |
—
|
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: 1998 Johannesburg – men’s 100 metres | Statement: [Maurice Greene, IAAFWorldCupGoldMedal, 1998 Johannesburg – men’s 100 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: IAAFWorldCupGoldMedal Context triple: [Maurice Greene, IAAFWorldCupGoldMedal, 1998 Johannesburg – men’s 100 metres]
-
A.
worldChampionshipsGoldMedal
Indicates that the subject has won a gold medal at a world championship competition.
-
B.
worldChampionshipGoldMedals
Indicates the number of gold medals an entity has won at world championship competitions.
-
C.
WorldCupMedal
Indicates that an entity has received a medal (e.g., gold, silver, bronze) for its performance in a FIFA World Cup tournament.
-
D.
WorldChampionshipGoldMedalYear
Indicates the specific year in which an entity won a gold medal at a world championship event.
-
E.
allAfricaGamesGoldMedal
Indicates that the subject has won a gold medal at the All-Africa Games.
- F. None of above. chosen
Provenance (4 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142d6fb588190b4176eab4bbae774 |
completed | April 16, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69e173af801c8190bfc0f602831bb594 |
completed | April 16, 2026, 11:41 p.m. |
Created at: April 10, 2026, 4:54 a.m.