Triple
T33344499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Republic of Zubrowka |
E853758
|
entity |
| Predicate | hasFictionalMountainRange |
P198554
|
FINISHED |
| Object | Zubrowkan Alps |
—
|
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: Zubrowkan Alps | Statement: [Republic of Zubrowka, hasFictionalMountainRange, Zubrowkan Alps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalMountainRange Context triple: [Republic of Zubrowka, hasFictionalMountainRange, Zubrowkan Alps]
-
A.
hasFictionalMountain
chosen
Indicates that one entity includes, features, or is associated with a fictional mountain as part of its content, setting, or description.
-
B.
hasMountainRange
Indicates that one entity possesses, contains, or is geographically associated with a specific mountain range.
-
C.
mountainRange
Indicates that one entity is a mountain range that the other entity is part of, associated with, or located in.
-
D.
sourceMountainRange
Indicates that a river, stream, or similar feature originates from or has its source in a specified mountain range.
-
E.
mountainRangeType
Indicates the classification or category of a mountain range based on its geological or geographical type.
- 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_69f3496a1a588190bad9cbe9221144e0 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff17be6ad48190963206f2619b1b28 |
completed | May 9, 2026, 11:17 a.m. |
| PD | Predicate disambiguation | batch_69ff1724ba24819092c928fcbcb286ec |
completed | May 9, 2026, 11:14 a.m. |
Created at: May 1, 2026, 1:34 a.m.