Triple
T16753500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lena Nyman |
E407147
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Lena Nyman |
E407147
|
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: Lena Nyman | Statement: [Lena Nyman, name, Lena Nyman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lena Nyman Context triple: [Lena Nyman, name, Lena Nyman]
-
A.
Lena Nyman
chosen
Lena Nyman was a Swedish actress known for her emotionally intense and nuanced performances in both film and theater, particularly in influential Scandinavian cinema of the 1960s and 1970s.
-
B.
Lena Nilsson
Lena Nilsson is a Swedish actress known for her work in film, television, and theater.
-
C.
Lena Ek
Lena Ek is a Swedish Centre Party politician and former Minister for the Environment in Sweden.
-
D.
Kristina Lugn
Kristina Lugn was a Swedish poet, playwright, and member of the Swedish Academy known for her darkly humorous and psychologically incisive works.
-
E.
Eva Persson
Eva Persson is a notable individual bearing the Swedish surname Persson, recognized for her contributions in her respective field.
- 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_69d8839174188190909f190097207065 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3aa28fd3c8190972e2e69ea7dece0 |
completed | April 18, 2026, 3:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a525e57881908e9e9453e6d6eb73 |
completed | May 10, 2026, 3:32 p.m. |
Created at: April 10, 2026, 5:21 a.m.