Triple
T16231421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lacey Schwimmer |
E393990
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Schwimmer |
E391144
|
NE 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: Schwimmer | Statement: [Lacey Schwimmer, familyName, Schwimmer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schwimmer Context triple: [Lacey Schwimmer, familyName, Schwimmer]
-
A.
Schwimmer
chosen
Schwimmer is a German-origin surname borne by various notable individuals in fields such as acting, politics, and activism.
-
B.
Nuotaea
Nuotaea is a small village settlement located on the atoll of Abaiang in the island nation of Kiribati.
-
C.
Speedo
Speedo is a globally recognized swimwear and aquatic sports brand known for its performance-focused swimsuits and gear used by elite swimmers.
-
D.
SWIM
SWIM is a subsystem within the SARA framework, likely responsible for a specific functional module such as data handling, communication, or workflow management.
-
E.
Reinhardt Schwimmer
Reinhardt Schwimmer was an optometrist and mob associate who was among the seven men murdered in Chicago’s infamous 1929 Saint Valentine’s Day Massacre.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e23d29fa248190943f4c3f7808908b |
completed | April 17, 2026, 2:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0007a0ab08819082aea4c312c9ffc7 |
completed | May 10, 2026, 4:20 a.m. |
Created at: April 10, 2026, 5:04 a.m.