Triple
T31542160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caroline Evers-Swindell |
E804773
|
entity |
| Predicate | competesInBoatClass |
P37610
|
FINISHED |
| Object | double scull |
—
|
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: double scull | Statement: [Caroline Evers-Swindell, competesInBoatClass, double scull]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: competesInBoatClass Context triple: [Caroline Evers-Swindell, competesInBoatClass, double scull]
-
A.
sailingClass
Indicates that one entity is a type or category of sailing activity, vessel, or competition class to which the other entity belongs or is associated.
-
B.
boatRaceRole
Indicates the specific role or function an entity has within the context of a boat race (e.g., participant, organizer, official).
-
C.
competedInDiscipline
chosen
Indicates that an entity took part in a competition or event within a specific discipline or category.
-
D.
hasRowingSide
Indicates that an entity involved in rowing is associated with a specific side (e.g., port or starboard) on which it rows.
-
E.
competesInDivision
Indicates that an entity participates in competitive activities within a specified division or tier of a larger organizational or league structure.
- 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_69f348d11a048190a65eb8384a3754ac |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f7516d5b4081908588a6feb541f355 |
completed | May 3, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69f74d40ebb081909daf60623e38f41d |
completed | May 3, 2026, 1:27 p.m. |
Created at: April 30, 2026, 10:06 p.m.