Triple
T33581107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mervyn King (darts player) |
E860148
|
entity |
| Predicate | hasCareer |
P198381
|
FINISHED |
| Object | long-term darts 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: long-term darts career | Statement: [Mervyn King (darts player), hasCareer, long-term darts career]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCareer Context triple: [Mervyn King (darts player), hasCareer, long-term darts career]
-
A.
hasCareerService
Indicates that an entity provides or is associated with a career-related support or advisory service for another entity.
-
B.
hasProfessionalCareer
chosen
Indicates that an entity engages in or has engaged in a recognized professional occupation or career over a period of time.
-
C.
hasCareerFunction
Indicates that an entity performs, is associated with, or is responsible for a specific career-related role or function.
-
D.
hasCareerStage
Indicates the specific phase or stage of a person's or entity's professional or occupational progression.
-
E.
hasCareerTrack
Indicates that an entity is associated with or follows a particular career path or professional progression.
- 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_69f3497d37848190afcbb5ef3f5c7376 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff2fbae9b48190847eefa1c227d43e |
completed | May 9, 2026, 12:59 p.m. |
| PD | Predicate disambiguation | batch_69ff2f2218048190a32224a648182b5d |
completed | May 9, 2026, 12:57 p.m. |
Created at: May 1, 2026, 1:40 a.m.