Triple
T5270905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imatra |
E119253
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Salzgitter |
E75169
|
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: Salzgitter | Statement: [Imatra, hasTwinTown, Salzgitter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Salzgitter Context triple: [Imatra, hasTwinTown, Salzgitter]
-
A.
Salzgitter
chosen
Salzgitter is a major industrial city in central Germany known for its steel production and location within the federal state of Lower Saxony.
-
B.
Recklinghausen
Recklinghausen is a city in the Ruhr area of North Rhine-Westphalia, western Germany, known historically for coal mining and its role as a regional administrative center.
-
C.
Eisenhüttenstadt
Eisenhüttenstadt is an industrial planned city in eastern Germany, known for its large steelworks and postwar socialist urban design.
-
D.
Clausthal
Clausthal is a historic mining town in Lower Saxony, Germany, best known today for its technical university and association with figures like microbiologist Robert Koch.
-
E.
Hagen
Hagen is a city in the Ruhr region of North Rhine-Westphalia in western Germany, known historically as an industrial and transport hub.
- 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_69bd446c38e081908cdaf113bdf86790 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7c1fa01081909d589686289b624b |
completed | March 20, 2026, 4:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69befe9691608190bae0865f80e23062 |
completed | March 21, 2026, 8:24 p.m. |
Created at: March 20, 2026, 1:51 p.m.