Triple
T13851206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna Kashfi |
E332944
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Anna Kashfi |
E332944
|
NE FINISHED |
How this triple was built (2 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: Anna Kashfi | Statement: [Anna Kashfi, name, Anna Kashfi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anna Kashfi Context triple: [Anna Kashfi, name, Anna Kashfi]
-
A.
Anna Kashfi
chosen
Anna Kashfi was a British-Indian actress and the first wife of Hollywood star Marlon Brando.
-
B.
Kinan Azmeh
Kinan Azmeh is a Syrian clarinetist and composer known for blending classical, jazz, and Middle Eastern musical traditions in his performances and compositions.
-
C.
Mona Khalidi
Mona Khalidi is known primarily as the wife of Palestinian-American historian and Columbia University professor Rashid Khalidi.
-
D.
Safia Farkash
Safia Farkash is the second wife of former Libyan leader Muammar Gaddafi and the mother of several of his children, known primarily for her role as Libya’s de facto first lady during his rule.
-
E.
Aida El-Kachef
Aida El-Kachef is known as the wife of Egyptian diplomat and Nobel Peace Prize laureate Mohamed ElBaradei.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d81c5ba13c8190839315f54768acfd |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02d8fb788190baef7537be2baecb |
completed | April 14, 2026, 9:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce6c0c3c8190911b56b20c9eb955 |
completed | May 3, 2026, 10:38 p.m. |
Created at: April 9, 2026, 10:14 p.m.