Triple
T11240330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korsholm |
E266054
|
entity |
| Predicate | hasNeighbouringMunicipality |
P224
|
FINISHED |
| Object | Malax |
E208454
|
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: Malax | Statement: [Korsholm, hasNeighbouringMunicipality, Malax]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Malax Context triple: [Korsholm, hasNeighbouringMunicipality, Malax]
-
A.
Malax
chosen
Malax is a small coastal municipality in western Finland known for its Swedish-speaking majority and rural Ostrobothnian landscapes.
-
B.
Landana
Landana is a coastal town in Angola’s Cabinda exclave, historically known as a regional trading and missionary center.
-
C.
Mawanella
Mawanella is a town in central Sri Lanka known as a key transit point on the Colombo–Kandy road and for its surrounding rubber and tea plantations.
-
D.
Malaco
Malaco is a popular Scandinavian confectionery brand known for its wide range of candies and licorice products.
-
E.
Mandraki
Mandraki is the main town and administrative center of the Greek island of Nisyros, known for its traditional architecture and seaside setting.
- 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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e919eaf48190a1457851cfc56afb |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4ad79e4788190af39186f37600a64 |
completed | April 19, 2026, 10:24 a.m. |
Created at: April 8, 2026, 9:30 p.m.