Triple
T19421425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franekeraner |
E485862
|
entity |
| Predicate | culturalRegion |
P1968
|
FINISHED |
| Object | Westergo |
—
|
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: Westergo | Statement: [Franekeraner, culturalRegion, Westergo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Westergo Context triple: [Franekeraner, culturalRegion, Westergo]
-
A.
Westergo
chosen
Westergo is a historic region in the province of Friesland in the northern Netherlands, traditionally encompassing several important medieval towns and rural areas.
-
B.
Borregaard
Borregaard is a Norwegian biorefinery company that produces advanced and sustainable bio-based chemicals and materials from wood.
-
C.
Wossek
Wossek is a small town in what is now the Czech Republic, historically part of the Austro-Hungarian Empire and known as the birthplace of Hermann Kafka, father of writer Franz Kafka.
-
D.
Hasselager
Hasselager is a residential neighborhood in the southern part of Aarhus, Denmark.
-
E.
Globba
Globba is a genus of tropical flowering plants in the ginger family, known for its ornamental, often pendulous inflorescences.
- 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_69d8e8d688f881909c85104a62e09d8a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63214d768819082129100d7116521 |
completed | April 20, 2026, 2:03 p.m. |
Created at: April 10, 2026, 1:37 p.m.