Triple
T21741088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gabriel Batistuta |
E536659
|
entity |
| Predicate | totalInternationalCaps |
P102809
|
FINISHED |
| Object | 78 |
—
|
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: 78 | Statement: [Gabriel Batistuta, totalInternationalCaps, 78]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalInternationalCaps Context triple: [Gabriel Batistuta, totalInternationalCaps, 78]
-
A.
internationalFootballCaps
chosen
Indicates the number of official international football (soccer) matches a player has appeared in for their national team.
-
B.
WorldCupAppearances
Indicates the number of times an entity has participated in FIFA World Cup final tournaments.
-
C.
nationalTeamAppearances
Indicates the number of official matches in which an entity has represented its national team.
-
D.
worldCupAppearancesCount
Indicates the number of times an entity has participated in the FIFA World Cup tournament.
-
E.
worldCupAppearances
Indicates the number of times an entity has participated in a FIFA World Cup tournament.
- 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_69e0c46df5448190b4322127ffc4c690 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01a7250d48190aa63f89db017ef70 |
completed | April 28, 2026, 2:24 a.m. |
| PD | Predicate disambiguation | batch_69e6969c16fc8190b5126c169317d85d |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:49 p.m.