Triple
T4169558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ede |
E84526
|
entity |
| Predicate | hasNeighbouringMunicipality |
P224
|
FINISHED |
| Object | Renkum |
E395212
|
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: Renkum | Statement: [Ede, hasNeighbouringMunicipality, Renkum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Renkum Context triple: [Ede, hasNeighbouringMunicipality, Renkum]
-
A.
Renkum
chosen
Renkum is a municipality and town in the province of Gelderland in the eastern Netherlands, known for its riverside landscapes and proximity to the city of Arnhem.
-
B.
Kromï
Kromï is a Russian locality historically notable as a key center of the Bolotnikov Rebellion in the early 17th century.
-
C.
Kioni
Kioni is a picturesque seaside village on the Greek island of Ithaca, known for its traditional architecture and scenic harbor.
-
D.
Runkel
Runkel is a small historic town in the German state of Hesse, known for its medieval hilltop castle overlooking the Lahn River.
-
E.
Kortgene
Kortgene is a small town in the Dutch province of Zeeland, known as an administrative and recreational center on the island of Noord-Beveland.
- 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_69aed932cab48190b80ffe35f7029ae1 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02c730b081908b19e6a4aea1549b |
completed | March 9, 2026, 5:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f4c2c988190959496cc0cc31cac |
completed | March 14, 2026, 3:31 p.m. |
Created at: March 9, 2026, 3:44 p.m.