Triple
T5528617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Premier League under-21 team |
E144988
|
entity |
| Predicate | professionalEnvironment |
P65275
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Premier League under-21 team, professionalEnvironment, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalEnvironment Context triple: [Premier League under-21 team, professionalEnvironment, yes]
-
A.
professionalSector
Indicates the industry or field in which an entity conducts its professional or occupational activities.
-
B.
professional
Indicates that one entity has a formal, occupation-related role, service, or expertise in relation to another entity.
-
C.
businessCareer
Indicates a relationship where an entity’s professional life, roles, or progression is specifically within the field of business or commerce.
-
D.
professionalHead
Indicates that one entity serves as the primary professional leader or chief authority over another entity within an organizational or occupational context.
-
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. 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_69c008f9955881909bfa8348b56b4739 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f8b6c348190b7d414dc1907d09a |
completed | March 22, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69c01b0a06348190b39ac9fe80d2836a |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f051e508190b3886d87b4afdd0b |
completed | March 22, 2026, 4:55 p.m. |
Created at: March 22, 2026, 3:34 p.m.