Triple
T20666991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Doto |
E507917
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Joe A. Doto |
E506809
|
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: Joe A. Doto | Statement: [Joe Doto, alsoKnownAs, Joe A. Doto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joe A. Doto Context triple: [Joe Doto, alsoKnownAs, Joe A. Doto]
-
A.
Joe A. Doto
chosen
Joe A. Doto, better known as Joe Adonis, was a prominent Italian-American mobster and influential figure in organized crime during the early to mid-20th century.
-
B.
Earl K. Fernandes
Earl K. Fernandes is an American Roman Catholic prelate who serves as the bishop of the Diocese of Columbus, Ohio.
-
C.
George A. Mendoza
George A. Mendoza is a film producer best known for his work on Disney’s animated feature "The Lion King 1½."
-
D.
Joe M. Aguilar
Joe M. Aguilar is a film producer best known for his work on the animated feature "Puss in Boots."
-
E.
Frank C. Ortis
Frank C. Ortis is an American politician best known for serving as the long-time mayor of Pembroke Pines, Florida.
- 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_69e0b4c059bc81908ea762cd73ea4424 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b5c39dd48190965d65537592aef6 |
completed | April 20, 2026, 11:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08cd6271e481909e3a6f10ec40ce11 |
completed | May 16, 2026, 8:02 p.m. |
Created at: April 16, 2026, 11:44 a.m.