Triple
T8528490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aalborg |
E201878
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Rendsburg |
E228981
|
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: Rendsburg | Statement: [Aalborg, hasTwinTown, Rendsburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rendsburg Context triple: [Aalborg, hasTwinTown, Rendsburg]
-
A.
Rendsburg
chosen
Rendsburg is a historic town in northern Germany known for its strategic location on the Kiel Canal and its distinctive high railway bridge.
-
B.
Lauenburg
Lauenburg is a historic town in northern Germany situated on the banks of the Elbe River.
-
C.
Borghorst
Borghorst is a district of the German town Steinfurt in North Rhine-Westphalia, known historically for its textile industry and regional cultural heritage.
-
D.
Neumünster
Neumünster is a mid-sized industrial and commercial city in northern Germany known for its textile history and central location within Schleswig-Holstein.
-
E.
Oldenburg
Oldenburg is a historic university city in northwestern Germany known for its cultural heritage and role as a regional economic center.
- 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_69ca83228b24819085d22e7dc99f5d94 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe672e0588190a84328e1bf974f08 |
completed | March 31, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce6d54ef908190970a1010c8018abd |
completed | April 2, 2026, 1:21 p.m. |
Created at: March 30, 2026, 6:17 p.m.