Triple
T12446865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarstedt |
E297421
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Ritterhude |
E689604
|
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: Ritterhude | Statement: [Sarstedt, hasTwinTown, Ritterhude]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ritterhude Context triple: [Sarstedt, hasTwinTown, Ritterhude]
-
A.
Ritterhude
chosen
Ritterhude is a small town in northern Germany’s Lower Saxony, situated just northwest of Bremen.
-
B.
Dierdorf
Dierdorf is a surname most prominently associated with former American football player and sportscaster Dan Dierdorf.
-
C.
Duisdorf
Duisdorf is a district of Bonn, Germany, known as a residential area with local commerce and public services within the borough of Hardtberg.
-
D.
Ochtrup
Ochtrup is a small town in the Münster region of North Rhine-Westphalia in western Germany, known for its textile industry and designer outlet center.
-
E.
Rheydt
Rheydt is a district of the German city of Mönchengladbach in North Rhine-Westphalia, historically an independent town in the Rhineland.
- 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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d90f18c819083a36ff4b9be4a20 |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a16408081909097d7e3ab750a27 |
completed | May 3, 2026, 8:40 a.m. |
Created at: April 8, 2026, 9:56 p.m.