Triple
T5310117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ricarda |
E119001
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object | Rikarda |
E119001
|
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: Rikarda | Statement: [Ricarda, hasVariantSpelling, Rikarda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rikarda Context triple: [Ricarda, hasVariantSpelling, Rikarda]
-
A.
Ricarda
chosen
Ricarda is a feminine given name, primarily used in German- and Spanish-speaking countries, derived from the male name Richard.
-
B.
Kaarina
Kaarina is a town and municipality in southwestern Finland, located near the city of Turku.
-
C.
Katja
Katja is a diminutive or short form of the given name Katarina, commonly used in various Slavic and European languages.
-
D.
Kristina
Kristina is a feminine given name commonly used in various European countries, often considered a variant of Christina.
-
E.
Karin
Karin is a feminine given name used in various cultures, often considered a variant of names like Karen or Katherine.
- 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_69bd446b57bc8190a513d2e6c40314f3 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8532c26c819084f5b8de542cd309 |
completed | March 20, 2026, 5:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf10ffb1f08190aba4c1c860085c92 |
completed | March 21, 2026, 9:43 p.m. |
Created at: March 20, 2026, 1:53 p.m.