Triple
T22746732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wales, Alaska |
E562573
|
entity |
| Predicate | distanceToRussia |
P21939
|
FINISHED |
| Object | approximately 55 miles across the Bering Strait |
—
|
LITERAL 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: approximately 55 miles across the Bering Strait | Statement: [Wales, Alaska, distanceToRussia, approximately 55 miles across the Bering Strait]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToRussia Context triple: [Wales, Alaska, distanceToRussia, approximately 55 miles across the Bering Strait]
-
A.
distanceToRussianBorder_km
chosen
Indicates the physical distance, measured in kilometers, between a given location and the nearest point on the Russian border.
-
B.
distanceToVladivostok_km
Indicates the physical distance, measured in kilometers, between a given location and Vladivostok.
-
C.
distanceFromMoscow_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Moscow.
-
D.
distanceToArkhangelskApproxKm
Indicates the approximate distance, measured in kilometers, between a given entity’s location and Arkhangelsk.
-
E.
distanceFromSaintPetersburg
Indicates the spatial distance between a given entity and the city of Saint Petersburg.
- F. None of above.
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_69e245513a5c81908d5cb471b4fc429d |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f179b634b88190906edd92a971f921 |
completed | April 29, 2026, 3:23 a.m. |
| PD | Predicate disambiguation | batch_69eed2b88d88819096015deb6a648801 |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:24 p.m.