Triple
T3183939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margarita |
E66654
|
entity |
| Predicate | hasVariantForm |
P457
|
FINISHED |
| Object | Margaretha |
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: Margaretha | Statement: [Margarita, hasVariantForm, Margaretha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Margaretha Context triple: [Margarita, hasVariantForm, Margaretha]
-
A.
Margareta
chosen
Margareta is a feminine given name used in various European languages, closely related to and derived from the name Margaret.
-
B.
Violanta
Violanta is a one-act opera by Erich Wolfgang Korngold, known for its lush late-Romantic score and psychologically intense drama set in Renaissance Venice.
-
C.
Gisela
Gisela was a daughter of Charlemagne, the Frankish king and first Holy Roman Emperor, and a member of the Carolingian royal family.
-
D.
Hedvig
Hedvig is a Scandinavian female given name, historically borne by several notable women in Swedish and broader Nordic royalty and nobility.
-
E.
Ricarda
Ricarda is a feminine given name, primarily used in German- and Spanish-speaking countries, derived from the male name Richard.
- 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_69ad8587c1bc8190a2595f2c22ee1001 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada6bfc4248190af320471688c60f0 |
completed | March 8, 2026, 4:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2620b62f48190905812d0c0e9f85c |
completed | March 12, 2026, 6:49 a.m. |
Created at: March 8, 2026, 3:06 p.m.