Triple
T10390801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Detention |
E244886
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
MaryAnn Tanedo
MaryAnn Tanedo is a film producer best known for her work on the movie "Detention."
|
E858925
|
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: MaryAnn Tanedo | Statement: [Detention, producer, MaryAnn Tanedo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MaryAnn Tanedo Context triple: [Detention, producer, MaryAnn Tanedo]
-
A.
Patricia Alvaran
Patricia Alvaran is known as the former wife of American actor Tom Berenger.
-
B.
Elaine Okamura
Elaine Okamura is best known as the first wife of American singer and entertainer Wayne Newton, whom she married in the 1960s before their later divorce.
-
C.
Linda Garcia
Linda Garcia is known primarily as the daughter of Carlos P. Garcia, the eighth President of the Philippines.
-
D.
Karen Peralta
Karen Peralta is a character in the television series "Brooklyn Nine-Nine," known as the mother of main protagonist Jake Peralta.
-
E.
Lori Matsuoka
Lori Matsuoka is best known as the wife of Hall of Fame basketball player and sportscaster Bill Walton and for her involvement in charitable and philanthropic activities.
- 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: MaryAnn Tanedo Triple: [Detention, producer, MaryAnn Tanedo]
Generated description
MaryAnn Tanedo is a film producer best known for her work on the movie "Detention."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MaryAnn Tanedo Target entity description: MaryAnn Tanedo is a film producer best known for her work on the movie "Detention."
-
A.
Patricia Alvaran
Patricia Alvaran is known as the former wife of American actor Tom Berenger.
-
B.
Elaine Okamura
Elaine Okamura is best known as the first wife of American singer and entertainer Wayne Newton, whom she married in the 1960s before their later divorce.
-
C.
Linda Garcia
Linda Garcia is known primarily as the daughter of Carlos P. Garcia, the eighth President of the Philippines.
-
D.
Karen Peralta
Karen Peralta is a character in the television series "Brooklyn Nine-Nine," known as the mother of main protagonist Jake Peralta.
-
E.
Lori Matsuoka
Lori Matsuoka is best known as the wife of Hall of Fame basketball player and sportscaster Bill Walton and for her involvement in charitable and philanthropic activities.
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9b4f7d08190bcb16d3b4c8f22ad |
completed | April 7, 2026, 11:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d795b9974c819087340adc3622279e |
completed | April 9, 2026, 12:04 p.m. |
| NEDg | Description generation | batch_69d7985e7fc081909fd1ba1dc6f7338c |
completed | April 9, 2026, 12:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d799917ab881909a947ad8059652c6 |
completed | April 9, 2026, 12:20 p.m. |
Created at: April 6, 2026, 12:06 p.m.