Triple
T15479618
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kassis |
E376879
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Nayla Kassis
Nayla Kassis is a person bearing the surname Kassis, noted as a distinct individual associated with that family name.
|
E1159721
|
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: Nayla Kassis | Statement: [Kassis, hasNotableBearer, Nayla Kassis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nayla Kassis Context triple: [Kassis, hasNotableBearer, Nayla Kassis]
-
A.
Nayla Moawad
Nayla Moawad is a Lebanese politician and former First Lady known for her advocacy of sovereignty, democracy, and women's rights in Lebanon.
-
B.
Mona Khalidi
Mona Khalidi is known primarily as the wife of Palestinian-American historian and Columbia University professor Rashid Khalidi.
-
C.
Lila Yacoub
Lila Yacoub is a film producer known for her work on independent features such as Noah Baumbach’s comedy-drama "Mistress America."
-
D.
Leila Helou
Leila Helou is a character in Jonathan Franzen’s novel "Purity," involved in the book’s intricate web of personal relationships and political intrigue.
-
E.
Lyna Khoudri
Lyna Khoudri is an Algerian-French actress known for her acclaimed performances in films such as "Papicha" and Wes Anderson’s "The French Dispatch."
- 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: Nayla Kassis Triple: [Kassis, hasNotableBearer, Nayla Kassis]
Generated description
Nayla Kassis is a person bearing the surname Kassis, noted as a distinct individual associated with that family name.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nayla Kassis Target entity description: Nayla Kassis is a person bearing the surname Kassis, noted as a distinct individual associated with that family name.
-
A.
Nayla Moawad
Nayla Moawad is a Lebanese politician and former First Lady known for her advocacy of sovereignty, democracy, and women's rights in Lebanon.
-
B.
Mona Khalidi
Mona Khalidi is known primarily as the wife of Palestinian-American historian and Columbia University professor Rashid Khalidi.
-
C.
Lila Yacoub
Lila Yacoub is a film producer known for her work on independent features such as Noah Baumbach’s comedy-drama "Mistress America."
-
D.
Leila Helou
Leila Helou is a character in Jonathan Franzen’s novel "Purity," involved in the book’s intricate web of personal relationships and political intrigue.
-
E.
Lyna Khoudri
Lyna Khoudri is an Algerian-French actress known for her acclaimed performances in films such as "Papicha" and Wes Anderson’s "The French Dispatch."
- 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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f8a77a081909f12f13660452f4a |
completed | April 16, 2026, 1:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff2d0b3e7881908f195701fe222371 |
completed | May 9, 2026, 12:48 p.m. |
| NEDg | Description generation | batch_69ff2e4010dc8190b0f81d03acf8ba41 |
completed | May 9, 2026, 12:53 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff310c2d5c819093295c45307176ec |
completed | May 9, 2026, 1:05 p.m. |
Created at: April 10, 2026, 3:34 a.m.