Triple
T20018300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fræna |
E494779
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Aukra |
—
|
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: Aukra | Statement: [Fræna, borderedBy, Aukra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aukra Context triple: [Fræna, borderedBy, Aukra]
-
A.
Aukra
chosen
Aukra is a coastal municipality in western Norway known for its fishing industry and offshore petroleum-related activities.
-
B.
Rausu
Rausu is a small coastal town on Japan’s Shiretoko Peninsula, known for its rich marine wildlife, drift ice sightseeing, and access to the remote natural landscapes of eastern Hokkaido.
-
C.
Avusy
Avusy is a small rural municipality located in the canton of Geneva in southwestern Switzerland, near the French border.
-
D.
Auzas
Auzas is a small commune in southwestern France, located in the Haute-Garonne department within the Occitanie region.
-
E.
Balta
Balta is a city that gained historical significance as a strategic location captured during the Uman–Botoșani offensive in World War II.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6623e40748190b1abb0ead9acab4e |
completed | April 20, 2026, 5:28 p.m. |
Created at: April 11, 2026, 3:34 p.m.