Triple
T12166878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Szymon |
E289855
|
entity |
| Predicate | hasDiminutiveFormInPolish |
P456
|
FINISHED |
| Object | Szymek |
—
|
LITERAL 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: Szymek | Statement: [Szymon, hasDiminutiveFormInPolish, Szymek]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiminutiveFormInPolish Context triple: [Szymon, hasDiminutiveFormInPolish, Szymek]
-
A.
hasDiminutive
chosen
Indicates that one entity is a diminutive form or smaller/affectionate variant of another entity.
-
B.
hasNameInPolish
Indicates that an entity is associated with a specific name or label expressed in the Polish language.
-
C.
hasFemaleFormOf
Indicates that one entity is the specifically female version or form of another, more general or differently gendered entity.
-
D.
hasKashubianName
Indicates that an entity is associated with a specific name in the Kashubian language.
-
E.
hasFeminineFormInCzechAndSlovak
Indicates that an entity has a specifically feminine grammatical or lexical form in the Czech and Slovak languages.
- 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_69d6ab4d6c00819095a9a7c35de83cfb |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91621ca6c81908365732f361aef13 |
completed | April 10, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69d9150e85348190b9b47cda4a17dcd0 |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:50 p.m.