Triple
T15623113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dina Shihabi |
E375610
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Dina Shihabi |
E375610
|
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: Dina Shihabi | Statement: [Dina Shihabi, name, Dina Shihabi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dina Shihabi Context triple: [Dina Shihabi, name, Dina Shihabi]
-
A.
Dina Shihabi
chosen
Dina Shihabi is a Saudi Arabian–born actress known for her prominent roles in American film and television, including the series "Jack Ryan."
-
B.
Dina Dalal
Dina Dalal is a fiercely independent, middle-aged Parsi widow in Mumbai whose struggle to maintain autonomy amid political turmoil and social injustice forms the emotional core of Rohinton Mistry’s novel *A Fine Balance*.
-
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.
Nayla Kassis
Nayla Kassis is a person bearing the surname Kassis, noted as a distinct individual associated with that family name.
-
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.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e9cfd94819091459aa17a002eaf |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff5f3da754819085a6bd9876b12c65 |
completed | May 9, 2026, 4:22 p.m. |
Created at: April 10, 2026, 4:14 a.m.