Triple
T19444696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weissensee |
E486442
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Carinthia |
E108550
|
NE 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: Carinthia | Statement: [Weissensee, locatedIn, Carinthia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carinthia Context triple: [Weissensee, locatedIn, Carinthia]
-
A.
Carinthia
chosen
Carinthia is a mountainous federal state in southern Austria known for its Alpine landscapes, lakes, and outdoor tourism.
-
B.
Tyrol
Tyrol is a mountainous federal state in western Austria, renowned for its Alpine landscapes, ski resorts, and hiking regions.
-
C.
East Tyrol
East Tyrol is a mountainous district in the Austrian state of Tyrol, known for its Alpine landscapes, hiking and skiing areas, and relatively sparse population.
-
D.
Styria
Styria is a federal state in southeastern Austria known for its capital Graz, diverse landscapes, and strong industrial and educational sectors.
-
E.
Western Tyrol
Western Tyrol is a mountainous region in western Austria known for its high Alpine peaks, including the Wildspitze, and popular ski and hiking areas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6338921cc819083f8f918225d78e6 |
completed | April 20, 2026, 2:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a075ef735bc8190b7fdebafd73f9f90 |
completed | May 15, 2026, 5:59 p.m. |
Created at: April 10, 2026, 1:38 p.m.