Triple
T4663609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All American |
E102791
|
entity |
| Predicate | star |
P23405
|
FINISHED |
| Object |
Monet Mazur
Monet Mazur is an American actress and model best known for her film and television roles, including a lead role on the sports drama series "All American."
|
E460649
|
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: Monet Mazur | Statement: [All American, star, Monet Mazur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monet Mazur Context triple: [All American, star, Monet Mazur]
-
A.
Juliana Minsky
Juliana Minsky is a daughter of pioneering artificial intelligence researcher Marvin Minsky.
-
B.
Miriam Weinstein
Miriam Weinstein is the mother of film producer Harvey Weinstein, whose first name inspired the name of the film company Miramax.
-
C.
Alisande Ullman
Alisande Ullman is best known as the former wife of Canadian-American comedic actor Leslie Nielsen.
-
D.
Eleanor Sokoloff
Eleanor Sokoloff was a renowned American pianist and long-serving pedagogue celebrated for training generations of leading pianists at the Curtis Institute of Music.
-
E.
Therese Bloch
Therese Bloch was the wife of prominent American Reform rabbi and Jewish leader Isaac Mayer Wise.
- 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: Monet Mazur Triple: [All American, star, Monet Mazur]
Generated description
Monet Mazur is an American actress and model best known for her film and television roles, including a lead role on the sports drama series "All American."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Monet Mazur Target entity description: Monet Mazur is an American actress and model best known for her film and television roles, including a lead role on the sports drama series "All American."
-
A.
Juliana Minsky
Juliana Minsky is a daughter of pioneering artificial intelligence researcher Marvin Minsky.
-
B.
Miriam Weinstein
Miriam Weinstein is the mother of film producer Harvey Weinstein, whose first name inspired the name of the film company Miramax.
-
C.
Alisande Ullman
Alisande Ullman is best known as the former wife of Canadian-American comedic actor Leslie Nielsen.
-
D.
Eleanor Sokoloff
Eleanor Sokoloff was a renowned American pianist and long-serving pedagogue celebrated for training generations of leading pianists at the Curtis Institute of Music.
-
E.
Therese Bloch
Therese Bloch was the wife of prominent American Reform rabbi and Jewish leader Isaac Mayer Wise.
- 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_69bd43d9cba4819086c1ab1c2d9d2133 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd632d6150819085bab97021c0235a |
completed | March 20, 2026, 3:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be03803a948190b6dc2a03bb9cdc93 |
completed | March 21, 2026, 2:33 a.m. |
| NEDg | Description generation | batch_69be0542daf08190b792855c8129ac50 |
completed | March 21, 2026, 2:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be05c1dcd48190a08a5748e86a5ac8 |
completed | March 21, 2026, 2:43 a.m. |
Created at: March 20, 2026, 1:15 p.m.