Triple
T6058577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hiiu County |
E134974
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Käina |
E141439
|
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: Käina | Statement: [Hiiu County, contains, Käina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Käina Context triple: [Hiiu County, contains, Käina]
-
A.
Käina
chosen
Käina is a small settlement on the Estonian island of Hiiumaa, known for its coastal landscapes and traditional rural character.
-
B.
Kaa
Kaa is a giant, hypnotic python who serves as a dangerous and manipulative predator in Disney’s live-action adaptation of The Jungle Book.
-
C.
Kesbewa
Kesbewa is a suburban town in Sri Lanka’s Western Province, situated within the greater Colombo metropolitan area.
-
D.
Senaki
Senaki is a town in western Georgia that serves as an important local administrative and transportation center in the Samegrelo region.
-
E.
Kaiten
Kaiten was a Japanese warship that took part in the late-19th-century Boshin War naval engagements, including the Battle of Hakodate.
- 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_69c00877b6d4819096b0e163728b73a3 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0570e64408190ae7a2504f63bb58a |
completed | March 22, 2026, 8:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11d0e06288190b4389b43825d5929 |
completed | March 23, 2026, 10:59 a.m. |
Created at: March 22, 2026, 4:10 p.m.