Triple
T3786335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lost |
E85538
|
entity |
| Predicate | leadActor |
P1507
|
FINISHED |
| Object | Evangeline Lilly |
E256908
|
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: Evangeline Lilly | Statement: [Lost, leadActor, Evangeline Lilly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Evangeline Lilly Context triple: [Lost, leadActor, Evangeline Lilly]
-
A.
Evangeline Lilly
chosen
Evangeline Lilly is a Canadian actress best known for her roles in the television series "Lost" and as Hope van Dyne/The Wasp in the Marvel Cinematic Universe.
-
B.
Kate Beckinsale
Kate Beckinsale is an English actress known for her versatile film career, including prominent roles in action, drama, and comedy films such as the Underworld series and various Hollywood productions.
-
C.
Shannon Elizabeth
Shannon Elizabeth is an American actress and former fashion model best known for her breakout role in the comedy film "American Pie."
-
D.
Ali Larter
Ali Larter is an American actress and former model best known for her roles in films like "Final Destination" and "Legally Blonde" and the TV series "Heroes."
-
E.
Teresa Palmer
Teresa Palmer is an Australian actress known for her roles in films such as "Warm Bodies," "Lights Out," and "Hacksaw Ridge."
- 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_69aed937fa8881908208ef3801060826 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee42d2bc88190ab85529fcd1aa20a |
completed | March 9, 2026, 3:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4fb1c90648190a76cee07508a83b9 |
completed | March 14, 2026, 6:07 a.m. |
Created at: March 9, 2026, 3:13 p.m.