Triple
T22982189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Barakat |
E571497
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Mary Barakat |
—
|
NE NERFINISHED |
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: Mary Barakat | Statement: [Mary Barakat, name, Mary Barakat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Barakat Context triple: [Mary Barakat, name, Mary Barakat]
-
A.
Mary Barakat
chosen
Mary Barakat is known primarily as the wife of renowned Egyptian film director Henry Barakat.
-
B.
Laila Fawzi
Laila Fawzi was an Egyptian actress and beauty queen known for her roles in classic Egyptian cinema during the mid-20th century.
-
C.
Salma Abu Deif
Salma Abu Deif is an Egyptian actress and model known for her roles in contemporary Arabic television series and films.
-
D.
Nahed Sherif
Nahed Sherif was a prominent Egyptian film actress known for her roles in popular Arabic cinema during the 1960s and 1970s.
-
E.
Dinah Madani
Dinah Madani is a determined and morally driven Homeland Security agent in Marvel's The Punisher series, known for her relentless pursuit of justice and uncovering government conspiracies.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245b3c50481908bb3741ec9f40862 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1829645f88190aea1b96ea595ff60 |
completed | April 29, 2026, 4:01 a.m. |
Created at: April 17, 2026, 3:49 p.m.