Triple
T36610813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gretel Bueta |
E903459
|
entity |
| Predicate | hasPlayedInternationalLevel |
P93578
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Gretel Bueta, hasPlayedInternationalLevel, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlayedInternationalLevel Context triple: [Gretel Bueta, hasPlayedInternationalLevel, true]
-
A.
playedInternationally
chosen
Indicates that an individual has participated in official international-level events or competitions representing a country or equivalent national entity.
-
B.
hasPlayedForNationalTeam
Indicates that an athlete has been a member of and appeared in competition for a specified national team.
-
C.
hasOfficiatedInternationalGames
Indicates that an individual has served as an official (e.g., referee, umpire, judge) in one or more international-level games or matches.
-
D.
hasPlayedInCountry
Indicates that an entity (typically a person or team) has participated in a game, match, or performance within a specified country.
-
E.
hasInternationalAchievements
Indicates that an entity has attained notable accomplishments or recognition at an international level.
- 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_69f76e6960e4819092047756ceb9a17e |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fdee770af48190aca2670db50f8b49 |
completed | May 8, 2026, 2:08 p.m. |
| PD | Predicate disambiguation | batch_69fdecec98a08190a357d816dc2a6dbe |
completed | May 8, 2026, 2:02 p.m. |
Created at: May 3, 2026, 4:11 p.m.