Triple
T19751122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Kymi |
E474373
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Kymi |
—
|
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: Kymi | Statement: [Port of Kymi, locatedIn, Kymi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kymi Context triple: [Port of Kymi, locatedIn, Kymi]
-
A.
Kymi
chosen
Kymi is a coastal town on the eastern side of the Greek island of Euboea, known for its port, scenic views, and role as a regional commercial center.
-
B.
Nayki
Nayki is an island located within Lake Rakshastal in the Tibet Autonomous Region of China.
-
C.
Kinnula
Kinnula is a small rural municipality in western Central Finland known for its forests, lakes, and outdoor recreation.
-
D.
Kallio
Kallio is a Finnish surname most notably borne by Kyösti Kallio, who served as the fourth President of Finland.
-
E.
Kallio
Kallio is a densely populated, historically working-class district in central Helsinki known for its vibrant nightlife, bohemian atmosphere, and diverse urban culture.
- 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_69d8e51940a0819087bd2996f98da668 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65299a7048190a9b22307ac06bd03 |
completed | April 20, 2026, 4:21 p.m. |
Created at: April 10, 2026, 1:48 p.m.