Triple
T21274848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna Vasa of Sweden |
E524361
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Vasa |
—
|
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: Vasa | Statement: [Anna Vasa of Sweden, familyName, Vasa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vasa Context triple: [Anna Vasa of Sweden, familyName, Vasa]
-
A.
Vasa
chosen
Vasa was a prominent royal dynasty in Sweden and Poland-Lithuania that produced several influential monarchs during the 16th and 17th centuries.
-
B.
Vasa (warship)
Vasa (warship) is a 17th-century Swedish warship that famously sank on its maiden voyage in 1628 and was later salvaged to become one of the world’s best-preserved historic ships.
-
C.
Marea Rosa
Marea Rosa is the Spanish term for the "Pink Tide," a wave of left-leaning and progressive governments that rose to prominence across Latin America in the early 21st century.
-
D.
Santa Maria de la mer
"Santa Maria de la mer" is a popular French song famously performed by chanteuse Mireille Mathieu.
-
E.
Pommern museum ship
The Pommern museum ship is a preserved early 20th-century four-masted steel barque, now serving as a maritime museum in Mariehamn, Åland.
- 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_69e0b516293c819089458ea2ec85f85e |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7365627a081908caea09097cca354 |
completed | April 21, 2026, 8:33 a.m. |
Created at: April 16, 2026, 4:01 p.m.