Triple
T19462715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernhard Eisel |
E486913
|
entity |
| Predicate | raceTypeStrength |
P136018
|
FINISHED |
| Object | one-day classics |
—
|
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: one-day classics | Statement: [Bernhard Eisel, raceTypeStrength, one-day classics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: raceTypeStrength Context triple: [Bernhard Eisel, raceTypeStrength, one-day classics]
-
A.
raceTypeDetail
Indicates the specific category or classification of a race, providing detailed information about the type of race involved in the relationship.
-
B.
raceTypeWon
Indicates the specific type or category of race that an entity has won.
-
C.
raceTypeBySex
Indicates that a race or competition is categorized or defined based on the sex of its participants.
-
D.
racecourseType
Indicates the specific kind or classification of a racecourse associated with an entity.
-
E.
raceCategory
Indicates the classification of an entity into a specific race or racial group within a defined categorization system.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633cd6c148190933b4d6bfe84cbe1 |
completed | April 20, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7499a4819082bec0be8afba35c |
completed | April 19, 2026, 4:06 p.m. |
| PDg | Predicate description generation | batch_69e5004c23308190a087b7941a90725f |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:38 p.m.