Triple
T21528788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freddie Thorp |
E531173
|
entity |
| Predicate | coStarredWith |
P14987
|
FINISHED |
| Object | Gaia Weiss |
—
|
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: Gaia Weiss | Statement: [Freddie Thorp, coStarredWith, Gaia Weiss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gaia Weiss Context triple: [Freddie Thorp, coStarredWith, Gaia Weiss]
-
A.
Gaia Weiss
chosen
Gaia Weiss is a French actress and model known for her roles in films and television series such as "Vikings" and various European productions.
-
B.
Gemma Donati
Gemma Donati was the Florentine noblewoman who became the wife of the Italian poet Dante Alighieri.
-
C.
Daria Cassini
Daria Cassini was the daughter of American actress Gene Tierney and fashion designer Oleg Cassini, known largely for her parents’ Hollywood and couture legacies.
-
D.
Athene Seyler
Athene Seyler was a distinguished English character actress known for her long stage and film career, often portraying eccentric or comedic older women.
-
E.
Zoe Moon
Zoe Moon is the central protagonist of the sitcom "Zoe Ever After," a newly single mother navigating life, love, and career after divorce.
- 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_69e0c45e5b8881908ac18fc2f493b114 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee8852e68c8190a5341c9f75081382 |
completed | April 26, 2026, 9:49 p.m. |
Created at: April 16, 2026, 6:27 p.m.