Triple
T14213650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Epic |
E352292
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Lori Forte
Lori Forte is a film producer best known for her work on the animated "Ice Age" franchise and other projects at Blue Sky Studios.
|
E1242868
|
NE FINISHED |
How this triple was built (4 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: Lori Forte | Statement: [Epic, producer, Lori Forte]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lori Forte Context triple: [Epic, producer, Lori Forte]
-
A.
Lori McCreary
Lori McCreary is an American film and television producer, co-founder of Revelations Entertainment, and longtime producing partner of actor Morgan Freeman.
-
B.
Lori Collins
Lori Collins is a central character in the comedy film "Ted," known as John Bennett’s long-suffering girlfriend who pushes him to grow up and choose between her and his crude, living teddy bear best friend.
-
C.
Lisa Vultaggio
Lisa Vultaggio is a Canadian actress best known for her role as Hannah Scott on the soap opera "General Hospital."
-
D.
Lori Martin
Lori Martin was an American actress best known for her role as the teenage daughter in the 1962 psychological thriller film "Cape Fear."
-
E.
Kate Forte
Kate Forte is a film and television producer best known for her work on projects such as the drama film "The Great Debaters."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lori Forte Triple: [Epic, producer, Lori Forte]
Generated description
Lori Forte is a film producer best known for her work on the animated "Ice Age" franchise and other projects at Blue Sky Studios.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lori Forte Target entity description: Lori Forte is a film producer best known for her work on the animated "Ice Age" franchise and other projects at Blue Sky Studios.
-
A.
Lori McCreary
Lori McCreary is an American film and television producer, co-founder of Revelations Entertainment, and longtime producing partner of actor Morgan Freeman.
-
B.
Lori Collins
Lori Collins is a central character in the comedy film "Ted," known as John Bennett’s long-suffering girlfriend who pushes him to grow up and choose between her and his crude, living teddy bear best friend.
-
C.
Lisa Vultaggio
Lisa Vultaggio is a Canadian actress best known for her role as Hannah Scott on the soap opera "General Hospital."
-
D.
Lori Martin
Lori Martin was an American actress best known for her role as the teenage daughter in the 1962 psychological thriller film "Cape Fear."
-
E.
Kate Forte
Kate Forte is a film and television producer best known for her work on projects such as the drama film "The Great Debaters."
- F. None of above. chosen
Provenance (5 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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de620f07bc81909212dcd1c91b5f95 |
completed | April 14, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d445c4848190b5c97bb27be6c749 |
completed | May 10, 2026, 6:53 p.m. |
| NEDg | Description generation | batch_6a00d4e10e848190aaa2a83012cb58ba |
completed | May 10, 2026, 6:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00d5adee908190a13bfc765e7c8f06 |
completed | May 10, 2026, 6:59 p.m. |
Created at: April 10, 2026, 1:06 a.m.