Triple
T5589133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yes, Dear |
E146831
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Greg Garcia |
E354821
|
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: Greg Garcia | Statement: [Yes, Dear, executiveProducer, Greg Garcia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greg Garcia Context triple: [Yes, Dear, executiveProducer, Greg Garcia]
-
A.
Greg Garcia
chosen
Greg Garcia is an American television writer and producer best known for creating the sitcom "My Name Is Earl."
-
B.
Jorge Garcia
Jorge Garcia is an American actor and comedian best known for his role as Hugo "Hurley" Reyes on the television series Lost.
-
C.
Miguel Ángel Ramírez
Miguel Ángel Ramírez is a Spanish football manager known for his tactical work in South American and Major League Soccer clubs.
-
D.
Antonio Negret
Antonio Negret is a Colombian film and television director known for action-driven projects such as the feature film "Overdrive" and episodes of popular TV series.
-
E.
Hector Elizondo
Hector Elizondo is an American character actor known for his versatile roles in film and television, including frequent collaborations with director Garry Marshall in movies like "Pretty Woman" and "The Princess Diaries."
- 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_69c009036c408190981a8d690b679b67 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0209ff5d88190843b6d134390ab71 |
completed | March 22, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07d8c6f8881909ac2018d11f5aef8 |
completed | March 22, 2026, 11:38 p.m. |
Created at: March 22, 2026, 3:38 p.m.