Triple
T2461504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mistress America |
E54543
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Lila Yacoub
Lila Yacoub is a film producer known for her work on independent features such as Noah Baumbach’s comedy-drama "Mistress America."
|
E269517
|
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: Lila Yacoub | Statement: [Mistress America, producer, Lila Yacoub]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lila Yacoub Context triple: [Mistress America, producer, Lila Yacoub]
-
A.
Lara Alameddine
Lara Alameddine is a film producer known for her work on the financial thriller "Money Monster."
-
B.
Aida El-Kachef
Aida El-Kachef is known as the wife of Egyptian diplomat and Nobel Peace Prize laureate Mohamed ElBaradei.
-
C.
Nelly Malek
Nelly Malek is best known as the mother of Academy Award–winning actor Rami Malek.
-
D.
Katherine Sarafian
Katherine Sarafian is an American film producer best known for her work at Pixar Animation Studios, including producing the Academy Award–winning feature "Brave."
-
E.
Rebekah Elmaloglou
Rebekah Elmaloglou is an Australian actress best known for her long-running role as Terese Willis on the soap opera "Neighbours."
- 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: Lila Yacoub Triple: [Mistress America, producer, Lila Yacoub]
Generated description
Lila Yacoub is a film producer known for her work on independent features such as Noah Baumbach’s comedy-drama "Mistress America."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lila Yacoub Target entity description: Lila Yacoub is a film producer known for her work on independent features such as Noah Baumbach’s comedy-drama "Mistress America."
-
A.
Lara Alameddine
Lara Alameddine is a film producer known for her work on the financial thriller "Money Monster."
-
B.
Aida El-Kachef
Aida El-Kachef is known as the wife of Egyptian diplomat and Nobel Peace Prize laureate Mohamed ElBaradei.
-
C.
Nelly Malek
Nelly Malek is best known as the mother of Academy Award–winning actor Rami Malek.
-
D.
Katherine Sarafian
Katherine Sarafian is an American film producer best known for her work at Pixar Animation Studios, including producing the Academy Award–winning feature "Brave."
-
E.
Rebekah Elmaloglou
Rebekah Elmaloglou is an Australian actress best known for her long-running role as Terese Willis on the soap opera "Neighbours."
- 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_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd11c47408190b10c7f6a151f2db2 |
completed | March 7, 2026, 7:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af179665d081909f9a761fa50c44e7 |
completed | March 9, 2026, 6:55 p.m. |
| NEDg | Description generation | batch_69af185baf5c8190b8aa3dc672f2e1be |
completed | March 9, 2026, 6:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69af18d8ab0881908ecd027080f96e0e |
completed | March 9, 2026, 7 p.m. |
Created at: March 6, 2026, 9:44 p.m.