Triple
T601298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MLS Cup |
E11498
|
entity |
| Predicate | professionalLevel |
P14125
|
FINISHED |
| Object | professional |
—
|
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: professional | Statement: [MLS Cup, professionalLevel, professional]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalLevel Context triple: [MLS Cup, professionalLevel, professional]
-
A.
professional
Indicates that one entity has a formal, occupation-related role, service, or expertise in relation to another entity.
-
B.
professionalTeam
Indicates that one entity is a professional sports team associated with, representing, or employing the other entity.
-
C.
trainingLevel
Indicates the degree or stage of training or skill development that an entity has attained.
-
D.
designationLevel
chosen
Indicates the specific rank, tier, or level assigned to an entity within a designation or classification system.
-
E.
professionalTitleAfterCompletion
Indicates that an entity is granted or holds a specific professional title as a result of successfully completing a particular program, course, or qualification.
- 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_69a4932779b881908688590d59c71900 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49e574444819087999404f3e3ffd9 |
completed | March 1, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69a49cf701e08190966d06b9ff4b582b |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.