Triple
T5867315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DaMarcus Beasley |
E130427
|
entity |
| Predicate | numberOfInternationalAppearances |
P13109
|
FINISHED |
| Object | 126 |
—
|
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: 126 | Statement: [DaMarcus Beasley, numberOfInternationalAppearances, 126]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfInternationalAppearances Context triple: [DaMarcus Beasley, numberOfInternationalAppearances, 126]
-
A.
nationalTeamAppearances
chosen
Indicates the number of official matches in which an entity has represented its national team.
-
B.
worldCupAppearances
Indicates the number of times an entity has participated in a FIFA World Cup tournament.
-
C.
WorldCupAppearances
Indicates the number of times an entity has participated in FIFA World Cup final tournaments.
-
D.
hasPlayedForNationalTeam
Indicates that an athlete has been a member of and appeared in competition for a specified national team.
-
E.
fifaWorldCupAppearances
Indicates the number of times an entity has participated in FIFA World Cup tournaments.
- 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_69c0085047dc8190af24e311edad3c07 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ffaef081909faaa7f420a3b9b7 |
completed | March 22, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69c03347e51c81909053bcf34e3b88ab |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:56 p.m.