Triple
T4856573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carinthia |
E108550
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Tyrol |
E449881
|
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: Tyrol | Statement: [Carinthia, borderedBy, Tyrol]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tyrol Context triple: [Carinthia, borderedBy, Tyrol]
-
A.
Tyrol
chosen
Tyrol is a mountainous federal state in western Austria, renowned for its Alpine landscapes, ski resorts, and hiking regions.
-
B.
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.
-
C.
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.
-
D.
Tirole
Tirole is the surname of Jean Tirole, a prominent French economist and Nobel laureate known for his work on industrial organization and regulation.
-
E.
Carinthia
Carinthia is a mountainous federal state in southern Austria known for its Alpine landscapes, lakes, and outdoor tourism.
- 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_69bd440a89548190a5f14ba6da6b97dc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d3df75c8190830e2c927cc5a4f8 |
completed | March 20, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bee059e7088190a04124e5918a3c42 |
completed | March 21, 2026, 6:15 p.m. |
Created at: March 20, 2026, 1:26 p.m.