Triple
T12836599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eemsmond |
E306931
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Helwerd |
E242558
|
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: Helwerd | Statement: [Eemsmond, containsSettlement, Helwerd]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helwerd Context triple: [Eemsmond, containsSettlement, Helwerd]
-
A.
Wassenberg
Wassenberg is a historic town in western Germany near the Dutch border, known for its medieval origins and association with the noble House of Wassenberg.
-
B.
Holwierde
chosen
Holwierde is a small village in the province of Groningen in the northern Netherlands, known for its historic terp (artificial dwelling mound) and medieval church.
-
C.
Wiehe
Wiehe is a small town in the German state of Thuringia, historically notable as the birthplace of the influential 19th-century historian Leopold von Ranke.
-
D.
Widdersberg
Widdersberg is a small village that forms one of the local subdivisions of the municipality of Münsing in Bavaria, Germany.
-
E.
Wildenberg
Wildenberg is a small municipality in the Kelheim district of Lower Bavaria, Germany, known for its rural character and agricultural surroundings.
- 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96ff015f4819090070a01f3938acc |
completed | April 10, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6a54838888190804202e45a55de48 |
completed | May 3, 2026, 1:30 a.m. |
Created at: April 9, 2026, 5:35 p.m.