Triple
T18568555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden Lions |
E453819
|
entity |
| Predicate | professionalBase |
P132569
|
FINISHED |
| Object | Johannesburg rugby structures |
—
|
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: Johannesburg rugby structures | Statement: [Golden Lions, professionalBase, Johannesburg rugby structures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalBase Context triple: [Golden Lions, professionalBase, Johannesburg rugby structures]
-
A.
professionalClass
Indicates that an entity belongs to, or is categorized within, a particular professional or occupational class.
-
B.
professionalHead
Indicates that one entity serves as the primary professional leader or chief authority over another entity within an organizational or occupational context.
-
C.
professional
Indicates that one entity has a formal, occupation-related role, service, or expertise in relation to another entity.
-
D.
professionalSince
Indicates the point in time when an entity began its professional activity or career in a given role or field.
-
E.
professionalCategory
Indicates the classification of an entity according to its professional field, role, or occupational domain.
- 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53affc3e08190b4d16b5ccb0bddbc |
completed | April 19, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69e478c16e0c8190b03966aa23c395a6 |
completed | April 19, 2026, 6:40 a.m. |
| PDg | Predicate description generation | batch_69e484121cd48190bf583b4c94636a30 |
completed | April 19, 2026, 7:28 a.m. |
Created at: April 10, 2026, 11:43 a.m.