Triple
T3351369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krimpen aan den IJssel |
E70499
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Ridderkerk |
E180392
|
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: Ridderkerk | Statement: [Krimpen aan den IJssel, borderedBy, Ridderkerk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ridderkerk Context triple: [Krimpen aan den IJssel, borderedBy, Ridderkerk]
-
A.
Ridderkerk
chosen
Ridderkerk is a town and municipality in the western Netherlands, situated near Rotterdam in the province of South Holland.
-
B.
Gilze en Rijen
Gilze en Rijen is a municipality and town in the southern Netherlands known for its proximity to Breda and its military air base.
-
C.
Soestdijk
Soestdijk is a village in the Netherlands known for its historic royal residence, Soestdijk Palace.
-
D.
’s-Heer Arendskerke
’s-Heer Arendskerke is a small village in the Dutch province of Zeeland, known for its rural character and historic church.
-
E.
Heiligenhaus
Heiligenhaus is a small town in North Rhine-Westphalia, western Germany, known for its manufacturing industry and location between Düsseldorf and Essen.
- 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_69ad85a4ef7c8190a29e2bbd6fa454e4 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb220721c81909eb4d8d35c923927 |
completed | March 8, 2026, 5:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b360a07dec819094b0645d0e2a91da |
completed | March 13, 2026, 12:56 a.m. |
Created at: March 8, 2026, 3:12 p.m.