Triple
T14311405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enschede |
E354840
|
entity |
| Predicate | hasNeighbouringMunicipality |
P224
|
FINISHED |
| Object | Losser |
E413748
|
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: Losser | Statement: [Enschede, hasNeighbouringMunicipality, Losser]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Losser Context triple: [Enschede, hasNeighbouringMunicipality, Losser]
-
A.
Losser
chosen
Losser is a municipality in the eastern Netherlands, located in the province of Overijssel near the German border.
-
B.
Loerzer
Loerzer is the surname of Bruno Loerzer, a notable German First World War flying ace and later Luftwaffe general.
-
C.
Lorens
Lorens is a character from Paulo Coelho’s novel "Brida," serving as one of the key figures in the protagonist’s spiritual and personal journey.
-
D.
Lunner
Lunner is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and role as part of the Hadeland traditional district.
-
E.
Kloss
Kloss is a surname most notably associated with Ilana Kloss, a former South African professional tennis player and sports executive.
- 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_69d8278ed42c8190b9f882dcce611347 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de85b386d0819087d14f3ce84a1997 |
completed | April 14, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3d3124488190b2ea35949294e297 |
completed | May 8, 2026, 1:32 a.m. |
Created at: April 10, 2026, 1:12 a.m.