Triple
T15965081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pat Croce |
E387165
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Pat Croce |
E387165
|
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: Pat Croce | Statement: [Pat Croce, name, Pat Croce]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pat Croce Context triple: [Pat Croce, name, Pat Croce]
-
A.
Pat Croce
chosen
Pat Croce is an American entrepreneur, motivational speaker, and former president and part-owner of the NBA’s Philadelphia 76ers.
-
B.
Steve Crosetti
Steve Crosetti is a fictional Baltimore homicide detective known for his intense personality and strong Catholic faith on the television series "Homicide: Life on the Street."
-
C.
Greg Corrado
Greg Corrado is an American computer scientist and researcher known for his pioneering work in artificial intelligence and deep learning, including co-founding Google Brain.
-
D.
Dan Cracchiolo
Dan Cracchiolo is a film producer known for his work on action movies, including the Steven Seagal vehicle "Exit Wounds."
-
E.
Max Ferraro
Max Ferraro is a recurring character on the sitcom "One Day at a Time," known as a charming EMT and the on-and-off romantic partner of Penelope Alvarez.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e157258b3c8190a72c868bd055ed94 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe84f4888190b3fdb5f32763f78d |
completed | May 9, 2026, 11:08 p.m. |
Created at: April 10, 2026, 4:54 a.m.