Triple
T13435321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Baltimore Aquatic Club |
E320214
|
entity |
| Predicate | notableAthlete |
P10392
|
FINISHED |
| Object | Michael Phelps |
E86200
|
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: Michael Phelps | Statement: [North Baltimore Aquatic Club, notableAthlete, Michael Phelps]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Phelps Context triple: [North Baltimore Aquatic Club, notableAthlete, Michael Phelps]
-
A.
Michael Phelps
chosen
Michael Phelps is an American swimmer widely regarded as the most decorated Olympian of all time, known for his record-breaking medal haul and dominance in multiple Olympic Games.
-
B.
Mark Spitz
Mark Spitz is an American former competitive swimmer who became legendary for winning seven gold medals at the 1972 Munich Olympics, a record at the time.
-
C.
Jon Ledecky
Jon Ledecky is an American businessman and investor best known as a co-owner of the NHL’s New York Islanders.
-
D.
Rob Dressel
Rob Dressel is a cinematographer best known for his work on the animated film "Big Hero 6."
-
E.
Phelps
Phelps is a surname that may refer to various individuals, including fictional characters such as Aunt Polly from classic literature.
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaee29fec81908b07b4fca2922242 |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f739902d148190ac14ac66f1f9512f |
completed | May 3, 2026, 12:03 p.m. |
Created at: April 9, 2026, 9:40 p.m.