Triple
T3835127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Josefa |
E91111
|
entity |
| Predicate | cognateWith |
P2525
|
FINISHED |
| Object | Josepha |
E91111
|
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: Josepha | Statement: [Josefa, cognateWith, Josepha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Josepha Context triple: [Josefa, cognateWith, Josepha]
-
A.
Josefa
chosen
Josefa is a feminine given name of Spanish origin, historically borne by notable figures such as Mexican independence heroine Josefa Ortiz de Domínguez.
-
B.
Terézia
Terézia is the given name of the Hungarian-born German writer and translator Terézia Mora, known for her award-winning novels and screenplays.
-
C.
Mária
Mária is the Hungarian and Slovak form of the given name Mary, commonly used in Central and Eastern Europe.
-
D.
Franziska
Franziska is a feminine given name of German origin, closely related to and cognate with the name Frances.
-
E.
Hermine Santruschitz
Hermine Santruschitz, better known as Miep Gies, was one of the Dutch citizens who helped hide Anne Frank and her family during World War II and preserved Anne’s diary after their arrest.
- 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_69aed960b538819096561c8ed448dec9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeb9a27508190b05e5312cc7c8033 |
completed | March 9, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b50402b2448190aef242c46bf0546d |
completed | March 14, 2026, 6:45 a.m. |
Created at: March 9, 2026, 3:18 p.m.