Triple
T16533730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DDR-Oberliga |
E401631
|
entity |
| Predicate | wasAmateurOrSemiPro |
P123931
|
FINISHED |
| Object | semi-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: semi-professional | Statement: [DDR-Oberliga, wasAmateurOrSemiPro, semi-professional]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasAmateurOrSemiPro Context triple: [DDR-Oberliga, wasAmateurOrSemiPro, semi-professional]
-
A.
isAmateur
Indicates that an entity engages in an activity or field on a non-professional, typically unpaid or hobbyist basis.
-
B.
hasAmateurLevel
Indicates that an entity possesses an amateur level of skill, experience, or proficiency in a given activity or domain.
-
C.
hasProAm
Indicates that an entity possesses or is associated with a professional–amateur (pro-am) status, feature, or component.
-
D.
historicallyAmateurUntil
Indicates that an entity was considered amateur, rather than professional, up to a specified point in time.
-
E.
semiProfessionalTiers
Indicates a relationship in which entities are organized or classified into tiers that represent semi-professional levels or statuses.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32eda42548190be61efb25a44a554 |
completed | April 18, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69e2969fab208190ad64164d24748c45 |
completed | April 17, 2026, 8:22 p.m. |
| PDg | Predicate description generation | batch_69e2d7f97e548190a474691a152bd8e8 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:15 a.m.