Triple
T19501112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gretel |
E487902
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Grete |
—
|
NE NERFINISHED |
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: Grete | Statement: [Gretel, hasVariant, Grete]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grete Context triple: [Gretel, hasVariant, Grete]
-
A.
Grete
chosen
Grete is the given name of Grete Hermann, a German mathematician and philosopher known for her pioneering work in the foundations of quantum mechanics and computer algebra.
-
B.
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.
-
C.
Grete Mosheim
Grete Mosheim was a prominent Austrian-German stage and film actress of the early 20th century, known for her work in both European and later British cinema and theatre.
-
D.
Gitte
Gitte is a feminine given name commonly used in Scandinavian countries, particularly Denmark.
-
E.
Gjertrud
Gjertrud is a feminine given name of Germanic origin, most notably borne by the American poet Gjertrud Schnackenberg.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6350ce7cc819086d77bbd9cd52b53 |
completed | April 20, 2026, 2:15 p.m. |
Created at: April 10, 2026, 1:40 p.m.