Triple
T38009143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olympic football qualification for Europe |
E948315
|
entity |
| Predicate | usesAgeCategory |
P125218
|
FINISHED |
| Object | men's under-23 with over-age exceptions |
—
|
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: men's under-23 with over-age exceptions | Statement: [Olympic football qualification for Europe, usesAgeCategory, men's under-23 with over-age exceptions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesAgeCategory Context triple: [Olympic football qualification for Europe, usesAgeCategory, men's under-23 with over-age exceptions]
-
A.
ageGroupIndicated
chosen
Indicates that a specific age range or category is identified or assigned to an entity.
-
B.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
-
C.
canAge
Indicates that one entity has the capability or property of undergoing aging over time.
-
D.
supportsAgeRange
Indicates that one entity is compatible with, valid for, or designed to accommodate a specified range of ages.
-
E.
ageCategoryDefinition
Indicates the rule or criteria that define how ages are grouped into specific age categories.
- 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_69f76efb4b10819092c8c2ba28ac06a8 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcc42cbac48190b8d3e4c9ce140838 |
completed | May 7, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69fcb0fc69c88190800453eb57a7e62c |
completed | May 7, 2026, 3:34 p.m. |
Created at: May 3, 2026, 4:20 p.m.