Triple
T21060279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yeonpyeong Island |
E518830
|
entity |
| Predicate | distanceToNorthKoreaCoast |
P15760
|
FINISHED |
| Object | close to North Korean mainland coast |
—
|
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: close to North Korean mainland coast | Statement: [Yeonpyeong Island, distanceToNorthKoreaCoast, close to North Korean mainland coast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToNorthKoreaCoast Context triple: [Yeonpyeong Island, distanceToNorthKoreaCoast, close to North Korean mainland coast]
-
A.
distanceToKoreanPeninsula
Indicates the measured or estimated spatial distance between a given entity or location and the Korean Peninsula.
-
B.
distanceFromCoast
chosen
Indicates the measured spatial separation between a location and the nearest point on a coastline.
-
C.
distanceFromMainland
Indicates the measured spatial separation between a location and the nearest point on the mainland.
-
D.
distanceToPacificOcean
Indicates the physical distance between a given location or entity and the Pacific Ocean.
-
E.
distanceToQatarCoast
Indicates the measured or calculated distance between a given location and the coastline of Qatar.
- 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_69e0b505ef108190b25dd4033e2ff7eb |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6feaf3edc81909423e039cac6bd87 |
completed | April 21, 2026, 4:35 a.m. |
| PD | Predicate disambiguation | batch_69e5dbf9d71881908cd85dfc37db93ca |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 2:37 p.m.