Triple
T15864359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilhelm von Homburg |
E384670
|
entity |
| Predicate | hasTypeOfCareer |
P55498
|
FINISHED |
| Object | sports career |
—
|
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: sports career | Statement: [Wilhelm von Homburg, hasTypeOfCareer, sports career]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfCareer Context triple: [Wilhelm von Homburg, hasTypeOfCareer, sports career]
-
A.
careerType
chosen
Indicates the kind or category of professional occupation or career path associated with an entity.
-
B.
hasTypicalOccupation
Indicates that an entity commonly or characteristically works in a particular job or profession.
-
C.
hasCareerService
Indicates that an entity provides or is associated with a career-related support or advisory service for another entity.
-
D.
targetCareer
Indicates that one entity is the intended or pursued career or professional goal of another entity.
-
E.
associatedWithCareerOf
Indicates a relationship where something is connected or relevant to a person’s professional life, occupation, or career trajectory.
- 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142b976c081908d3ba3e705419f3a |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:50 a.m.