Triple
T31453461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgina Evers-Swindell |
E802384
|
entity |
| Predicate | isTwinRowingPartnerOf |
P171891
|
FINISHED |
| Object | Caroline Evers-Swindell |
—
|
NE NERFINISHED |
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: Caroline Evers-Swindell | Statement: [Georgina Evers-Swindell, isTwinRowingPartnerOf, Caroline Evers-Swindell]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTwinRowingPartnerOf Context triple: [Georgina Evers-Swindell, isTwinRowingPartnerOf, Caroline Evers-Swindell]
-
A.
hasRowingSide
Indicates that an entity involved in rowing is associated with a specific side (e.g., port or starboard) on which it rows.
-
B.
partnerInLoveTeam
Indicates that two entities are teammates who are also partners in a romantic or love-based relationship.
-
C.
silverMedalistPairs
Indicates that the paired entities are the two competitors or teams who finished in second place (silver medal position) together in a given event or competition.
-
D.
spouseOfTeam
Indicates that one entity is the spouse of a member of the specified team.
-
E.
bronzeMedalistPairs
Indicates that the paired entities together achieved third place (bronze medal) in a given competition or event.
- 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_69f348c678ac81908a2e950867619061 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a5f71b2c8190aade8a83f465be0c |
completed | May 3, 2026, 1:33 a.m. |
| PD | Predicate disambiguation | batch_69f69fe66df08190958558d63ee623d9 |
completed | May 3, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69f6a5f656ec81909e02b0b873303adf |
completed | May 3, 2026, 1:33 a.m. |
Created at: April 30, 2026, 9:14 p.m.