Triple
T19788398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uprising |
E475337
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Mili Avital |
—
|
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: Mili Avital | Statement: [Uprising, stars, Mili Avital]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mili Avital Context triple: [Uprising, stars, Mili Avital]
-
A.
Mili Avital
chosen
Mili Avital is an Israeli-American actress known for her roles in film and television, including a prominent part in the science fiction movie "Stargate."
-
B.
Nili Priel
Nili Priel is an Israeli public figure best known as the wife of former Prime Minister and Defense Minister Ehud Barak.
-
C.
Karmei Tzur
Karmei Tzur is an Israeli settlement in the Gush Etzion region of the West Bank, located north of Hebron and known as a small religious community.
-
D.
Daliah Lavi
Daliah Lavi was an Israeli actress, singer, and model best known internationally for her roles in 1960s European and Hollywood films, particularly in stylish spy spoofs and adventure movies.
-
E.
Tamar Shalev
Tamar Shalev is known as the wife of the late Israeli author and columnist Meir Shalev.
- 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_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65389c9ac81909e61b3cbb9213e72 |
completed | April 20, 2026, 4:25 p.m. |
Created at: April 10, 2026, 1:49 p.m.