Triple
T18194951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gothia Cup |
E435634
|
entity |
| Predicate | ageGroupDivision |
P100475
|
FINISHED |
| Object | multiple age classes |
—
|
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: multiple age classes | Statement: [Gothia Cup, ageGroupDivision, multiple age classes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageGroupDivision Context triple: [Gothia Cup, ageGroupDivision, multiple age classes]
-
A.
ageGroup
Indicates the categorical age range or bracket to which an entity belongs.
-
B.
ageGroupStructure
Indicates how a population or set of entities is distributed across different age groups or age categories.
-
C.
ageGroupSystem
chosen
Indicates a classification relationship where entities are grouped according to a defined system of age-based categories.
-
D.
ageGroupInvolved
Indicates that a particular age group participates in, is affected by, or is otherwise involved in the specified event or relationship.
-
E.
ageGroupRole
Indicates the role or function an entity has within a specific age group classification.
- 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e0d1eb1c81908c20b6d15e9c4e8e |
completed | April 19, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69e4331e92408190ad607ba4956a3897 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:31 a.m.