Triple
T5021380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franeker |
E112857
|
entity |
| Predicate | locatedInRegion |
P40
|
FINISHED |
| Object |
Westergo
Westergo is a historic region in the province of Friesland in the northern Netherlands, traditionally encompassing several important medieval towns and rural areas.
|
E485858
|
NE FINISHED |
How this triple was built (4 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: [Franeker, locatedInRegion, Westergo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Westergo Context triple: [Franeker, locatedInRegion, Westergo]
-
A.
Borregaard
Borregaard is a Norwegian biorefinery company that produces advanced and sustainable bio-based chemicals and materials from wood.
-
B.
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.
-
C.
Pattensen
Pattensen is a small town in Lower Saxony, Germany, situated just south of Hanover in a predominantly rural and agricultural region.
-
D.
Petosega
Petosega is a family name most notably associated with Chief Ignatius Petosega, a historical Indigenous leader.
-
E.
Bergensten
Bergensten is the surname of Jens Bergensten, the Swedish video game programmer and lead developer known for his work on Minecraft.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Westergo Triple: [Franeker, locatedInRegion, Westergo]
Generated description
Westergo is a historic region in the province of Friesland in the northern Netherlands, traditionally encompassing several important medieval towns and rural areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Westergo Target entity description: Westergo is a historic region in the province of Friesland in the northern Netherlands, traditionally encompassing several important medieval towns and rural areas.
-
A.
Borregaard
Borregaard is a Norwegian biorefinery company that produces advanced and sustainable bio-based chemicals and materials from wood.
-
B.
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.
-
C.
Pattensen
Pattensen is a small town in Lower Saxony, Germany, situated just south of Hanover in a predominantly rural and agricultural region.
-
D.
Petosega
Petosega is a family name most notably associated with Chief Ignatius Petosega, a historical Indigenous leader.
-
E.
Bergensten
Bergensten is the surname of Jens Bergensten, the Swedish video game programmer and lead developer known for his work on Minecraft.
- F. None of above. chosen
Provenance (5 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_69bd4435c2f48190be593158cbfcf8a3 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd73656edc8190b802ad38d9552b58 |
completed | March 20, 2026, 4:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be927f4ad0819096826f6cb141c90b |
completed | March 21, 2026, 12:43 p.m. |
| NEDg | Description generation | batch_69be92e7304081909747a34dff7f9e25 |
completed | March 21, 2026, 12:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69be935872a88190adec17789298e01a |
completed | March 21, 2026, 12:47 p.m. |
Created at: March 20, 2026, 1:36 p.m.