Triple
T21301720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Attiswil |
E525080
|
entity |
| Predicate | hasNeighboringMunicipality |
P224
|
FINISHED |
| Object | Berken |
—
|
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: Berken | Statement: [Attiswil, hasNeighboringMunicipality, Berken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Berken Context triple: [Attiswil, hasNeighboringMunicipality, Berken]
-
A.
Berken
chosen
Berken is a small municipality in the Oberaargau region of the canton of Bern in Switzerland.
-
B.
Benkheim
Benkheim is the former German name for the village now known as Banie Mazurskie in northeastern Poland.
-
C.
Berar
Berar was a historical region in central India that became a significant Maratha-ruled province, later integrated into British India and now largely part of Maharashtra.
-
D.
Bergharen
Bergharen is a village in the Dutch province of Gelderland, known for its historic church and rural surroundings.
-
E.
Birkenes
Birkenes is a rural municipality in Agder county in southern Norway, known for its forests, rivers, and small villages.
- 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_69e0b517e6748190850d6f6ddf323d69 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7385cd6308190bf300494833b048f |
completed | April 21, 2026, 8:42 a.m. |
Created at: April 16, 2026, 4:05 p.m.