Triple
T5101098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ted Lasso |
E114981
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Juno Temple |
E389721
|
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: Juno Temple | Statement: [Ted Lasso, starring, Juno Temple]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Juno Temple Context triple: [Ted Lasso, starring, Juno Temple]
-
A.
Juno Temple
chosen
Juno Temple is an English actress known for her eclectic film roles and acclaimed performance as Keeley Jones in the television series "Ted Lasso."
-
B.
Haley Bennett
Haley Bennett is an American actress and singer known for her versatile performances in films such as "The Girl on the Train," "The Magnificent Seven," and "Swallow."
-
C.
Olivia DeJonge
Olivia DeJonge is an Australian actress known for her role as Priscilla Presley in Baz Luhrmann’s 2022 biographical film "Elvis."
-
D.
Samara Weaving
Samara Weaving is an Australian actress known for her roles in film and television, particularly in horror-comedy and thriller projects such as "Ready or Not" and "The Babysitter."
-
E.
Olivia Thirlby
Olivia Thirlby is an American actress known for her roles in films such as "Juno," "Dredd," and various independent and mainstream productions.
- 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_69bd4440b3348190be1251fd8b7951f1 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7584ed408190a6d1086588f24faa |
completed | March 20, 2026, 4:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bed915418c819083b6f304b7dd31db |
completed | March 21, 2026, 5:44 p.m. |
Created at: March 20, 2026, 1:40 p.m.