Triple
T30524234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karol Szymoniewicz Krokiew |
E776786
|
entity |
| Predicate | hasEponymousItem |
P56375
|
FINISHED |
| Object | Wielka Krokiew |
—
|
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: Wielka Krokiew | Statement: [Karol Szymoniewicz Krokiew, hasEponymousItem, Wielka Krokiew]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEponymousItem Context triple: [Karol Szymoniewicz Krokiew, hasEponymousItem, Wielka Krokiew]
-
A.
hasEponymousLabel
Indicates that something is named after a particular person, place, or entity, serving as its eponym.
-
B.
hasEponymType
Indicates that something is associated with or classified by a particular type of eponym (a name derived from a person).
-
C.
hasEponymCategory
Indicates that one entity serves as the namesake or eponym for the category or class represented by the other entity.
-
D.
hasEponymConnectionTo
chosen
Indicates that one entity is named after, derived from, or otherwise linguistically or honorifically connected to another entity as its eponym.
-
E.
hasEponymicConvention
Indicates that something is named according to an eponymic convention, i.e., derived from or based on the name of a person or entity.
- 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_69f2249b23c4819087fa85496d92f43f |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6880d55688190b742c534bc7d62d9 |
completed | May 2, 2026, 11:26 p.m. |
| PD | Predicate disambiguation | batch_69f67e42d6688190b60e91d2c388c555 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 29, 2026, 8:17 p.m.