Triple
T10225688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 9-1-1: Lone Star |
E243196
|
entity |
| Predicate | leadActor |
P1507
|
FINISHED |
| Object |
Natacha Karam
Natacha Karam is a British-Lebanese actress best known for her prominent television roles, including a main role on the procedural drama series "9-1-1: Lone Star."
|
E852799
|
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: Natacha Karam | Statement: [9-1-1: Lone Star, leadActor, Natacha Karam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Natacha Karam Context triple: [9-1-1: Lone Star, leadActor, Natacha Karam]
-
A.
Tania Nehme
Tania Nehme is an Australian film editor known for her work on acclaimed films such as the Indigenous Australian feature "Ten Canoes."
-
B.
Aliyah Khondji
Aliyah Khondji is a member of the Khondji family, known primarily as the daughter of acclaimed cinematographer Darius Khondji.
-
C.
Aida El-Kachef
Aida El-Kachef is known as the wife of Egyptian diplomat and Nobel Peace Prize laureate Mohamed ElBaradei.
-
D.
Mimi Chakib
Mimi Chakib was a prominent Egyptian film and stage actress known for her strong supporting roles in classic mid-20th-century Arabic cinema.
-
E.
Nelly Malek
Nelly Malek is best known as the mother of Academy Award–winning actor Rami Malek.
- 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: Natacha Karam Triple: [9-1-1: Lone Star, leadActor, Natacha Karam]
Generated description
Natacha Karam is a British-Lebanese actress best known for her prominent television roles, including a main role on the procedural drama series "9-1-1: Lone Star."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Natacha Karam Target entity description: Natacha Karam is a British-Lebanese actress best known for her prominent television roles, including a main role on the procedural drama series "9-1-1: Lone Star."
-
A.
Tania Nehme
Tania Nehme is an Australian film editor known for her work on acclaimed films such as the Indigenous Australian feature "Ten Canoes."
-
B.
Aliyah Khondji
Aliyah Khondji is a member of the Khondji family, known primarily as the daughter of acclaimed cinematographer Darius Khondji.
-
C.
Aida El-Kachef
Aida El-Kachef is known as the wife of Egyptian diplomat and Nobel Peace Prize laureate Mohamed ElBaradei.
-
D.
Mimi Chakib
Mimi Chakib was a prominent Egyptian film and stage actress known for her strong supporting roles in classic mid-20th-century Arabic cinema.
-
E.
Nelly Malek
Nelly Malek is best known as the mother of Academy Award–winning actor Rami Malek.
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d1f9cf6c81909a6b9e9b9d0a79fe |
completed | April 7, 2026, 9:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f715bea881909da9d0749fa6420f |
completed | April 9, 2026, 12:47 a.m. |
| NEDg | Description generation | batch_69d6fcaa16788190a4c7ef79a78febc6 |
completed | April 9, 2026, 1:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d6fd6d705c81908e469068937a79b3 |
completed | April 9, 2026, 1:14 a.m. |
Created at: April 6, 2026, 11:17 a.m.