Triple
T5592570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liga Nacional de Fútbol de Guatemala |
E146913
|
entity |
| Predicate | usesPointsSystem |
P64949
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Liga Nacional de Fútbol de Guatemala, usesPointsSystem, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesPointsSystem Context triple: [Liga Nacional de Fútbol de Guatemala, usesPointsSystem, yes]
-
A.
usesPointsForLoss
Indicates that a system or rule assigns or deducts points to represent or account for a loss.
-
B.
hasBadgeSystem
Indicates that an entity includes or supports a badge-based system for recognizing or tracking achievements, statuses, or milestones.
-
C.
usesCompetitionSystem
Indicates that an entity operates under or applies a particular competition system or format.
-
D.
hasExerciseRewardSystem
Indicates that an entity implements or is associated with a system that provides rewards or incentives for performing exercise or physical activity.
-
E.
pointsEarnedFrom
Indicates the number of points that an entity has received as a result of another specified source, action, or event.
- 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_69c009036c408190981a8d690b679b67 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020bb08648190ab1f66cc3e897e6d |
completed | March 22, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69c01b16b9bc8190ab0b945507d90e05 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f4032408190a4f0d2eb21ebd870 |
completed | March 22, 2026, 4:56 p.m. |
Created at: March 22, 2026, 3:38 p.m.