Triple
T4377087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gothia Cup |
E99032
|
entity |
| Predicate | ageGroupStructure |
P56466
|
FINISHED |
| Object | separate age classes by birth year |
—
|
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: separate age classes by birth year | Statement: [Gothia Cup, ageGroupStructure, separate age classes by birth year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageGroupStructure Context triple: [Gothia Cup, ageGroupStructure, separate age classes by birth year]
-
A.
ageGroup
Indicates the categorical age range or bracket to which an entity belongs.
-
B.
ageGroupRole
Indicates the role or function an entity has within a specific age group classification.
-
C.
populationClass
Indicates a categorical classification of a population based on shared characteristics, status, or demographic criteria.
-
D.
ageRange
Indicates the span of ages within which an entity or relationship is considered valid or applicable.
-
E.
portraysAgeGroup
Indicates that one entity depicts or represents another entity as belonging to a particular age group.
- 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_69b3454ea8f48190a49c2436624d6ef6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3523ed220819090cef1a7933489d9 |
completed | March 12, 2026, 11:54 p.m. |
| PD | Predicate disambiguation | batch_69b34f557fe8819085032bf7f0cea5dc |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b35034cd248190bae09e9d090e13ec |
completed | March 12, 2026, 11:45 p.m. |
Created at: March 12, 2026, 11:18 p.m.