Triple
T33302574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marysieńka |
E852625
|
entity |
| Predicate | affectionateDiminutiveOf |
P456
|
FINISHED |
| Object | Maria |
—
|
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: Maria | Statement: [Marysieńka, affectionateDiminutiveOf, Maria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affectionateDiminutiveOf Context triple: [Marysieńka, affectionateDiminutiveOf, Maria]
-
A.
hasAffectionateNicknameFor
Indicates that one entity uses or assigns a fond, affectionate, or endearing nickname to another entity.
-
B.
hasDiminutive
chosen
Indicates that one entity is a diminutive form or smaller/affectionate variant of another entity.
-
C.
affectionateHonorific
Indicates a relationship where one entity addresses or refers to another using a respectful title that also conveys warmth, fondness, or emotional closeness.
-
D.
childhoodNickname
Indicates that one entity is a nickname that was used to refer to the other entity during their childhood.
-
E.
honorificNickname
Indicates that one entity is referred to by a respectful or honorific nickname by another entity or in a given context.
- 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_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 1, 2026, 1:33 a.m.