Triple
T15714735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Region of Uusimaa |
E380931
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Askola |
E990212
|
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: Askola | Statement: [Region of Uusimaa, contains, Askola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Askola Context triple: [Region of Uusimaa, contains, Askola]
-
A.
Askola
chosen
Askola is a small rural municipality in southern Finland known for its agricultural landscape and proximity to the Helsinki metropolitan area.
-
B.
Askole
Askole is a remote high-altitude village in Pakistan’s Karakoram range that serves as a key gateway for trekking and mountaineering expeditions to major glaciers and peaks, including K2.
-
C.
Schulek
Schulek is a Hungarian surname most notably associated with architect and restorer János Schulek.
-
D.
Okulaja
Okulaja is a surname most notably associated with individuals of Nigerian or German-Nigerian heritage, including figures in sports and academia.
-
E.
Schull
Schull is a small coastal village and popular tourist destination on the Mizen Peninsula in West County Cork, Ireland.
- 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f90aea0819082a9e9fe0f7780b0 |
completed | April 16, 2026, 2:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff7581302c8190918266f04bcf2231 |
completed | May 9, 2026, 5:57 p.m. |
Created at: April 10, 2026, 4:45 a.m.