Triple
T15557507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salzgittersee |
E370907
|
entity |
| Predicate | isNear |
P350
|
FINISHED |
| Object | Salzgitter city center |
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 city center | Statement: [Salzgittersee, isNear, Salzgitter city center]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Salzgitter city center Context triple: [Salzgittersee, isNear, Salzgitter city center]
-
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.
Marktplatz, Hanover
Marktplatz, Hanover is the historic central market square of Hanover, Germany, known for its medieval architecture and role as a focal point of the Old Town.
-
C.
Bad Salzdetfurth
Bad Salzdetfurth is a spa town in Lower Saxony, Germany, known for its historic saltworks and therapeutic health resorts.
-
D.
Siemensstadt
Siemensstadt is a Berlin neighborhood historically shaped by the Siemens industrial works and noted for its early 20th-century modernist housing developments.
-
E.
Hansaplatz
Hansaplatz is a Berlin U-Bahn station on the U9 line located in the Hansaviertel district of the city.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04dda3ab88190ab383333ce69fe8f |
completed | April 16, 2026, 2:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff456427988190bddea01f5cb159d9 |
completed | May 9, 2026, 2:32 p.m. |
Created at: April 10, 2026, 4:09 a.m.