Triple
T2987117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boston Breakers |
E80651
|
entity |
| Predicate | notableCoach |
P550
|
FINISHED |
| Object | Tony DiCicco |
E161058
|
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: Tony DiCicco | Statement: [Boston Breakers, notableCoach, Tony DiCicco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tony DiCicco Context triple: [Boston Breakers, notableCoach, Tony DiCicco]
-
A.
Tony DiCicco
chosen
Tony DiCicco was an American soccer coach best known for leading the U.S. women’s national team to victory in the 1996 Olympics and the 1999 FIFA Women’s World Cup.
-
B.
Ernie Sabella
Ernie Sabella is an American actor and voice actor best known for voicing the warthog Pumbaa in Disney’s The Lion King franchise.
-
C.
Tony Gaudio
Tony Gaudio was an Italian-American cinematographer and early Hollywood pioneer known for his innovative camera work and Academy Award–winning contributions to classic films.
-
D.
Ray Ferraro
Ray Ferraro is a former Canadian professional ice hockey player and prominent NHL broadcaster known for his long playing career and work as a television analyst.
-
E.
Bob Giusti
Bob Giusti is an artist known for creating cover artwork, including the cover for the novel "It."
- 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_69ad8b16c3488190b47b6aa7a59a335b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99c88f608190bf734e0b744bf3d1 |
completed | March 8, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1eee1433c8190bdee291c12feeceb |
completed | March 11, 2026, 10:38 p.m. |
Created at: March 8, 2026, 2:59 p.m.