Triple
T11584873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess Tilde |
E274724
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Hanna Alström |
E56089
|
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: Hanna Alström | Statement: [Princess Tilde, portrayedBy, Hanna Alström]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hanna Alström Context triple: [Princess Tilde, portrayedBy, Hanna Alström]
-
A.
Hanna Alström
chosen
Hanna Alström is a Swedish actress best known internationally for her role as Princess Tilde in the action-comedy film "Kingsman: The Secret Service" and its sequel.
-
B.
Ylva Johansson
Ylva Johansson is a Swedish politician who has served as European Commissioner for Home Affairs and previously held several ministerial posts in the Swedish government.
-
C.
Greta Lundgren
Greta Lundgren is a daughter of Swedish actor and martial artist Dolph Lundgren.
-
D.
Anna-Lisa Hansson
Anna-Lisa Hansson was a daughter of Swedish Prime Minister Per Albin Hansson and a member of his prominent political family.
-
E.
Kristina Lugn
Kristina Lugn was a Swedish poet, playwright, and member of the Swedish Academy known for her darkly humorous and psychologically incisive works.
- 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_69d6aae6b14c81908dc5a74bad7591f9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d89462203881908870e991a5b21770 |
completed | April 10, 2026, 6:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef1307da188190918d0f50b2fd37fa |
completed | April 27, 2026, 7:40 a.m. |
Created at: April 8, 2026, 9:38 p.m.