Triple
T14145800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | spring classics |
E350544
|
entity |
| Predicate | riderSpecialization |
P15815
|
FINISHED |
| Object | classics specialists |
—
|
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: classics specialists | Statement: [spring classics, riderSpecialization, classics specialists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riderSpecialization Context triple: [spring classics, riderSpecialization, classics specialists]
-
A.
ridingSpecialty
chosen
Indicates that one entity has a particular area of expertise or focus related to riding (e.g., a specific riding style, discipline, or type).
-
B.
riderType
Indicates the category or role of a rider in relation to a ride, transport service, or vehicle (e.g., passenger, driver, courier).
-
C.
notableRiderType
Indicates that an entity is notably associated with a particular type or category of rider (e.g., cyclist, jockey, driver).
-
D.
unitSpecialization
Indicates that one unit is a specialized or more specific version of another unit within a hierarchical or categorical relationship.
-
E.
positionSpecialization
Indicates that one position is a more specialized or focused variant of another, broader position.
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de612266248190a8591b646fe30ae6 |
completed | April 14, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69de05b5e7a08190a16be9ad8b92b80c |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 12:53 a.m.