Triple
T16530348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NCAA Division II (women’s swimming and diving) |
E401545
|
entity |
| Predicate | levelRelativeToProfessional |
P90637
|
FINISHED |
| Object | amateur |
—
|
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: amateur | Statement: [NCAA Division II (women’s swimming and diving), levelRelativeToProfessional, amateur]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: levelRelativeToProfessional Context triple: [NCAA Division II (women’s swimming and diving), levelRelativeToProfessional, amateur]
-
A.
trainingLevel
Indicates the degree or stage of training or skill development that an entity has attained.
-
B.
semiProfessionalTiers
Indicates a relationship in which entities are organized or classified into tiers that represent semi-professional levels or statuses.
-
C.
typicalExperienceLevel
chosen
Indicates the usual or most common level of experience associated with an entity in a given context.
-
D.
professionalClass
Indicates that an entity belongs to, or is categorized within, a particular professional or occupational class.
-
E.
professionalScope
Indicates the range of activities, responsibilities, or roles that fall within a person’s or organization’s recognized professional duties or expertise.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32ed741088190a285f8f9431810f3 |
completed | April 18, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69e296995d388190b88ebe189dce890d |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:14 a.m.