Triple
T26185475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blake Snell |
E654815
|
entity |
| Predicate | genreOfStatisticalPerformance |
P163871
|
FINISHED |
| Object | run prevention specialist |
—
|
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: run prevention specialist | Statement: [Blake Snell, genreOfStatisticalPerformance, run prevention specialist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfStatisticalPerformance Context triple: [Blake Snell, genreOfStatisticalPerformance, run prevention specialist]
-
A.
genreOfStat
Indicates that a particular genre is the subject or category of a given statistical measurement or dataset.
-
B.
statisticalType
Indicates that one entity specifies the kind or category of statistical characterization or measurement that applies to another entity.
-
C.
statisticalScope
Indicates the statistical context or coverage within which a given measurement, observation, or statement is defined or valid.
-
D.
statisticsType
Indicates the specific kind or category of statistical measure or analysis associated with an entity or dataset.
-
E.
hasStatisticalRole
Indicates that an entity participates in a context (such as a study, dataset, or analysis) with a specific statistical function or role (e.g., variable, parameter, estimator).
- 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_69ee5b469bc081908fe486453fdad810 |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f6416fbf4081909b0913c337927fc4 |
completed | May 2, 2026, 6:24 p.m. |
| PD | Predicate disambiguation | batch_69f63c6456608190b94e7c2e2c2a4824 |
completed | May 2, 2026, 6:03 p.m. |
| PDg | Predicate description generation | batch_69f63fd4f7448190930c723ba7cfce62 |
completed | May 2, 2026, 6:17 p.m. |
Created at: April 26, 2026, 8:42 p.m.