Triple
T21208110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orissaare municipality |
E522642
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Orissaare |
—
|
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: Orissaare | Statement: [Orissaare municipality, hasSettlement, Orissaare]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orissaare Context triple: [Orissaare municipality, hasSettlement, Orissaare]
-
A.
Orissaare
chosen
Orissaare is a small town in western Estonia known for its coastal location on the island of Saaremaa.
-
B.
Landes
Landes is a department in southwestern France known for its vast Atlantic coastline, extensive pine forests, and popular surfing beaches.
-
C.
Ostrov
Ostrov is a town in the Karlovy Vary Region of the Czech Republic known for its historical architecture and proximity to the spa city of Karlovy Vary.
-
D.
Ostrov
Ostrov is a historic town in Pskov Oblast, Russia, known for its medieval architecture and role as a regional administrative and cultural center.
-
E.
Schwedeninsel
Schwedeninsel is a small, wooded island located in the Bavarian lake Ammersee in southern Germany.
- 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_69e0b5112d8881909510b2dcdc93106d |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e734362c788190bc1b96d3b84c0ad1 |
completed | April 21, 2026, 8:24 a.m. |
Created at: April 16, 2026, 3:25 p.m.