Triple
T10288305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marta (Scandinavian languages) |
E241293
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Märta |
E113357
|
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: Märta | Statement: [Marta (Scandinavian languages), hasVariant, Märta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Märta Context triple: [Marta (Scandinavian languages), hasVariant, Märta]
-
A.
Margareta
chosen
Margareta is a feminine given name used in various European languages, closely related to and derived from the name Margaret.
-
B.
Agneta
Agneta is a feminine given name, primarily used in Scandinavian countries, that is a variant of the name Agnes.
-
C.
Ottilia
Ottilia is a feminine given name of Germanic origin, related to Otto and typically interpreted to mean "wealth" or "prosperity."
-
D.
Gerda
Gerda is the brave and devoted young heroine of Hans Christian Andersen’s fairy tale who embarks on a perilous journey to rescue her friend Kai from the Snow Queen.
-
E.
Maud Olofsson
Maud Olofsson is a Swedish politician who served as leader of the Centre Party and as Deputy Prime Minister of Sweden in the 2000s.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2b9d76c8190b1ef6ecf4c1a2a09 |
completed | April 7, 2026, 9:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d794c79ae88190b80c805f7671e264 |
completed | April 9, 2026, noon |
Created at: April 6, 2026, 11:41 a.m.