Triple
T6625253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | golf correspondent of The Times |
E149781
|
entity |
| Predicate | occupationCategory |
P55498
|
FINISHED |
| Object | journalist |
—
|
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: journalist | Statement: [golf correspondent of The Times, occupationCategory, journalist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupationCategory Context triple: [golf correspondent of The Times, occupationCategory, journalist]
-
A.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
B.
careerType
chosen
Indicates the kind or category of professional occupation or career path associated with an entity.
-
C.
careerField
Indicates the professional domain or occupational area in which an entity works or specializes.
-
D.
genreOfOccupation
Indicates the specific genre or category that characterizes a particular occupation or professional role.
-
E.
usedByOccupation
Indicates that something (such as a tool, method, or resource) is utilized in the performance of a particular occupation or job.
- 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_69c687ee50048190aa151765bef16193 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6bdb88cc881908f35648c15a7dc85 |
completed | March 27, 2026, 5:26 p.m. |
| PD | Predicate disambiguation | batch_69c6ad007c1c8190af425f51011c7ad1 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:58 p.m.