Triple
T2984163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agdal |
E80581
|
entity |
| Predicate | notableBearer |
P458
|
FINISHED |
| Object | Nina Agdal |
E11517
|
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: Nina Agdal | Statement: [Agdal, notableBearer, Nina Agdal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nina Agdal Context triple: [Agdal, notableBearer, Nina Agdal]
-
A.
Nina Agdal
chosen
Nina Agdal is a Danish fashion model best known for her work with Sports Illustrated Swimsuit Issue and major international advertising campaigns.
-
B.
Sara Esberg
Sara Esberg is a television producer known for her executive production work on series such as the psychological horror show "Swarm."
-
C.
Kristina Lugn
Kristina Lugn was a Swedish poet, playwright, and member of the Swedish Academy known for her darkly humorous and psychologically incisive works.
-
D.
Nina Sosanya
Nina Sosanya is a British actress known for her work in television, film, and theatre, including roles in series such as "Last Tango in Halifax," "W1A," and "His Dark Materials."
-
E.
Hanna Alström
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.
- 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_69ad8b15f6ac8190be5fd16a33edcb4f |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99c481fc81909971c96352a881b4 |
completed | March 8, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b108f8b2b08190904cf89befe656dd |
completed | March 11, 2026, 6:17 a.m. |
Created at: March 8, 2026, 2:59 p.m.