Triple
T16246384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mala Osojnica |
E394380
|
entity |
| Predicate | hasPrimaryViewDirection |
P12663
|
FINISHED |
| Object | towards Lake Bled and Julian Alps |
—
|
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: towards Lake Bled and Julian Alps | Statement: [Mala Osojnica, hasPrimaryViewDirection, towards Lake Bled and Julian Alps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryViewDirection Context triple: [Mala Osojnica, hasPrimaryViewDirection, towards Lake Bled and Julian Alps]
-
A.
hasFieldOfView
Indicates that one entity possesses a visual coverage area within which it can perceive or detect other entities or regions.
-
B.
hasViewingSide
Indicates that one entity serves as the side or surface of another entity that is intended to be viewed or observed.
-
C.
hasViewingAngles
Indicates that one entity possesses or is characterized by specific viewing angles relative to another entity or reference frame.
-
D.
hasOrientation
chosen
Indicates that one entity is positioned or directed in a specific spatial or conceptual alignment relative to a reference frame or another entity.
-
E.
hasView
Indicates that one entity provides a visual perspective or outlook onto another entity or scene.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e245931074819096f38003da70f271 |
completed | April 17, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69e219ee6f6481909663b388dc99770a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:04 a.m.