Triple
T8573228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gertrude Ederle |
E202978
|
entity |
| Predicate | numberOfWorldRecordsSet |
P30976
|
FINISHED |
| Object | multiple |
—
|
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: multiple | Statement: [Gertrude Ederle, numberOfWorldRecordsSet, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfWorldRecordsSet Context triple: [Gertrude Ederle, numberOfWorldRecordsSet, multiple]
-
A.
worldRecordSet
Indicates that an entity has achieved and established the best performance ever recorded in the world for a particular activity, event, or measurable criterion.
-
B.
worldRecordSetOn
Indicates that a world record was achieved or established on a specific date or occasion.
-
C.
setWorldRecordsIn
Indicates that an entity has achieved and holds world record performances in a specified domain, event, or location.
-
D.
numberOfOlympicRecords
Indicates the count of Olympic records associated with a given entity.
-
E.
setWorldRecordCount
chosen
Indicates the number of times an entity has achieved or set a world record.
- 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_69ca8328ebe481909a8c038fa79959b4 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbea458c1081908e79bee2cbf97207 |
completed | March 31, 2026, 3:37 p.m. |
| PD | Predicate disambiguation | batch_69cbd11856048190a1ce4b83a38f6965 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:21 p.m.