Triple
T5492089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toronto FC II |
E123722
|
entity |
| Predicate | ageProfile |
P19123
|
FINISHED |
| Object | primarily young players |
—
|
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: primarily young players | Statement: [Toronto FC II, ageProfile, primarily young players]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageProfile Context triple: [Toronto FC II, ageProfile, primarily young players]
-
A.
ageDetail
Indicates a detailed specification of an entity’s age, such as exact value, range, or related age attributes.
-
B.
ageModel
Indicates a relationship where one entity specifies or provides the age of another entity, typically in terms of a particular age value or age-related classification.
-
C.
ageStatus
Indicates the relationship between an entity and its classification into an age-related category or status (e.g., minor, adult, senior).
-
D.
ageContext
Indicates the temporal or life-stage context in which an entity’s age is specified or interpreted.
-
E.
ageGroup
chosen
Indicates the categorical age range or bracket to which an entity belongs.
- 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_69bd464a2d908190869324ce176779c8 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd9280403c8190baaa3f7923449a37 |
completed | March 20, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69bd91a8df6481908d1643f7342fe6f0 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:10 p.m.