Triple
T17457342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wurzen Pass |
E425063
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Podkoren |
—
|
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: Podkoren | Statement: [Wurzen Pass, locatedNear, Podkoren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Podkoren Context triple: [Wurzen Pass, locatedNear, Podkoren]
-
A.
Podkoren
chosen
Podkoren is a small Alpine village in northwestern Slovenia, known for its picturesque setting near the Italian and Austrian borders and its proximity to popular natural and ski attractions.
-
B.
Radicava
Radicava is a prescription medication containing edaravone, used to slow the progression of amyotrophic lateral sclerosis (ALS) in adults.
-
C.
Korne
Korne is a river in the Netherlands on which the town of Buren is situated.
-
D.
Kök
Kök is a Turkish surname most notably borne by Mustafa Verşan Kök, a Turkish academic and university administrator.
-
E.
Kopaska
Kopaska is the Indonesian Navy’s elite frogman and special operations unit, specializing in underwater demolition, maritime sabotage, and counter-terrorism missions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889db0ba481908402409af3b37917 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e45142b08481908cdd290692d796c3 |
completed | April 19, 2026, 3:51 a.m. |
Created at: April 10, 2026, 5:47 a.m.