Triple
T36115838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kalle Rovanperä |
E1044611
|
entity |
| Predicate | becameFullTimeWRCDriverYear |
P185377
|
FINISHED |
| Object | 2020 |
—
|
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: 2020 | Statement: [Kalle Rovanperä, becameFullTimeWRCDriverYear, 2020]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: becameFullTimeWRCDriverYear Context triple: [Kalle Rovanperä, becameFullTimeWRCDriverYear, 2020]
-
A.
ranFullTime
Indicates that an entity was employed and worked on a full-time basis during a specified period.
-
B.
becameFullTimeMLBUmpire
Indicates that an individual transitioned into serving as a full-time umpire in Major League Baseball.
-
C.
introducedAsFullTimeService
Indicates that an entity has been formally brought into operation or offered on an ongoing basis as a full-time service.
-
D.
workYear
Indicates the specific year or span of years during which an entity (such as a person or organization) was engaged in work or employment.
-
E.
trainingCompletionYear
Indicates the calendar year in which an entity’s training program or course was completed.
- 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_69f76e344a4c8190af3858c6d78ba88f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be53890081909b1d93f30a8f31c6 |
completed | May 3, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69f7bccacbac8190978976324c67db28 |
completed | May 3, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69f7be520f148190ba200bf3dbf40656 |
completed | May 3, 2026, 9:29 p.m. |
Created at: May 3, 2026, 4:08 p.m.