Triple
T33302572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marysieńka |
E852625
|
entity |
| Predicate | givenNameVariantOf |
P161294
|
FINISHED |
| Object | Marie Casimire Louise de La Grange d’Arquien |
—
|
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: Marie Casimire Louise de La Grange d’Arquien | Statement: [Marysieńka, givenNameVariantOf, Marie Casimire Louise de La Grange d’Arquien]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: givenNameVariantOf Context triple: [Marysieńka, givenNameVariantOf, Marie Casimire Louise de La Grange d’Arquien]
-
A.
nameHasVariant
chosen
Indicates that an entity’s name has an alternative or variant form.
-
B.
EuropeanNameVariant
Indicates that one name is a variant or alternative form of another name as used in a European language or cultural context.
-
C.
givenName
Indicates the personal first name assigned to an individual.
-
D.
authorNameVariant
Indicates that an entity has an alternative or variant form of its author name, such as different spellings, transliterations, or name formats.
-
E.
surnameVariant
Indicates that one surname is an alternative spelling, form, or variation of another surname.
- F. None of above.
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_69f34966ed4c81908dc9dda82d8c7fe3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6f38159d08190980ad639e08f00f4 |
completed | May 3, 2026, 7:04 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d7bee48190b94e0beb48a1d7fa |
completed | May 3, 2026, 5:57 a.m. |
Created at: May 1, 2026, 1:33 a.m.