Triple
T910386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard |
E19643
|
entity |
| Predicate | hasFeminineForm |
P1613
|
FINISHED |
| Object | Richarda |
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: Richarda | Statement: [Richard, hasFeminineForm, Richarda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Richarda Context triple: [Richard, hasFeminineForm, Richarda]
-
A.
Ricarda
chosen
Ricarda is a feminine given name, primarily used in German- and Spanish-speaking countries, derived from the male name Richard.
-
B.
Johanna
Johanna is the given name of Johanna Spyri, the Swiss author best known for creating the classic children's novel "Heidi."
-
C.
Joanna
Joanna is the first name of Joanna Newsom, an American harpist, singer-songwriter, and musician known for her intricate compositions and distinctive vocal style.
-
D.
Franziska
Franziska is a feminine given name of German origin, closely related to and cognate with the name Frances.
-
E.
Luisa
Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
- 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_69a4939f91a08190ba68c2c81eab90fe |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2dca5208190bc9f17cd9dd6a98f |
completed | March 1, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac4282ea908190817857231b98f5b4 |
completed | March 7, 2026, 3:21 p.m. |
Created at: March 1, 2026, 7:39 p.m.