Triple
T20919349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Astrid Sofia Lovisa Thyra |
E515160
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Lovisa |
—
|
NE NERFINISHED |
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: Lovisa | Statement: [Astrid Sofia Lovisa Thyra, givenName, Lovisa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lovisa Context triple: [Astrid Sofia Lovisa Thyra, givenName, Lovisa]
-
A.
Lovisa
chosen
Lovisa is a historic coastal town in southern Finland known for its well-preserved wooden architecture and seaside charm.
-
B.
Liutperga
Liutperga was a Lombard princess, daughter of King Desiderius, known for her political role in the late Lombard kingdom of Italy.
-
C.
Dagmar
Dagmar is a feminine given name of Germanic origin, historically associated with European nobility and still used in various countries today.
-
D.
Edvarda
Edvarda is a central fictional character in Knut Hamsun’s novel "Pan," known for her complex and tumultuous relationship with the protagonist.
-
E.
Ludvika
Ludvika is a small industrial town in central Sweden known for its engineering and manufacturing industries, particularly in the power and electrical sectors.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4f9d5ec8190bb2bd27350ed341c |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6ec66593c819091ecf0c553e0aead |
completed | April 21, 2026, 3:17 a.m. |
Created at: April 16, 2026, 12:48 p.m.