Triple
T23521677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argentine football league system |
E574523
|
entity |
| Predicate | amateurLevel |
P91107
|
FINISHED |
| Object | regional and local leagues |
—
|
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: regional and local leagues | Statement: [Argentine football league system, amateurLevel, regional and local leagues]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: amateurLevel Context triple: [Argentine football league system, amateurLevel, regional and local leagues]
-
A.
hasAmateurLevel
Indicates that an entity possesses an amateur level of skill, experience, or proficiency in a given activity or domain.
-
B.
amateurTiers
chosen
Indicates a relationship where something is categorized or classified into levels or ranks designated for amateurs.
-
C.
isAmateur
Indicates that an entity engages in an activity or field on a non-professional, typically unpaid or hobbyist basis.
-
D.
amateurAchievement
Indicates that an entity has achieved something notable or commendable in a non-professional or hobbyist capacity.
-
E.
amateurTitle
Indicates that an entity holds or is associated with a non-professional (amateur) title or rank in a given domain or activity.
- 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_69e245bb3dcc8190ba9a2b35972b58d0 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1aa873ad48190a86807bd4f26df82 |
completed | April 29, 2026, 6:51 a.m. |
| PD | Predicate disambiguation | batch_69f1189d75b48190a1c01928a993c9fb |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:08 p.m.