Triple
T17442551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Písek |
E424693
|
entity |
| Predicate | locatedOnRiver |
P165
|
FINISHED |
| Object | Otava |
E386566
|
NE 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: Otava | Statement: [Písek, locatedOnRiver, Otava]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Otava Context triple: [Písek, locatedOnRiver, Otava]
-
A.
Otava
chosen
Otava is a major river in the Czech Republic that flows through southwestern Bohemia and is known for its scenic valleys, historical towns, and popularity for canoeing and recreation.
-
B.
Otava
Otava is a major Finnish publishing company known for producing a wide range of literature, non-fiction, and educational materials.
-
C.
Savukoski
Savukoski is a sparsely populated municipality in Finnish Lapland known for its vast wilderness areas and traditional reindeer herding culture.
-
D.
Sotkamo
Sotkamo is a municipality in eastern Finland known for its mining industry, outdoor recreation, and the popular Vuokatti ski and sports resort area.
-
E.
Kerava
Kerava is a small city in southern Finland known as a commuter town within the Greater Helsinki region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d889db0ba481908402409af3b37917 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44ff82bbc819095dd0621137da809 |
completed | April 19, 2026, 3:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a077eca55048190a7ff5ddfea12ed47 |
completed | May 15, 2026, 8:15 p.m. |
Created at: April 10, 2026, 5:47 a.m.