Triple
T3406453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsushima Island |
E71783
|
entity |
| Predicate | distanceToKoreanPeninsula |
P49111
|
FINISHED |
| Object | approximately 50 km |
—
|
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 50 km | Statement: [Tsushima Island, distanceToKoreanPeninsula, approximately 50 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToKoreanPeninsula Context triple: [Tsushima Island, distanceToKoreanPeninsula, approximately 50 km]
-
A.
distanceFromTokyo
Indicates the physical distance between a given location and Tokyo.
-
B.
distanceToContinentApproximate
Indicates an approximate measure of how far something is from a specified continent.
-
C.
distanceFromMainland
Indicates the measured spatial separation between a location and the nearest point on the mainland.
-
D.
distanceFromNewZealandMainland_km
Indicates the distance, measured in kilometers, between an entity’s location and the mainland of New Zealand.
-
E.
distanceFromKyoto
Indicates the measured spatial distance between a given entity’s location and the city of Kyoto.
- F. None of above. chosen
Provenance (4 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_69ad85aac4808190a092c9cc8911f584 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb8ec68c88190913df5f6cafad9e9 |
completed | March 8, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69adadfa73ac8190a163f93e88d217f8 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb21a437c81908bca88d5e123d744 |
completed | March 8, 2026, 5:30 p.m. |
Created at: March 8, 2026, 3:15 p.m.