Triple
T242765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rathaus Schöneberg |
E4968
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Schöneberg |
E13289
|
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: Schöneberg | Statement: [Rathaus Schöneberg, locatedIn, Schöneberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schöneberg Context triple: [Rathaus Schöneberg, locatedIn, Schöneberg]
-
A.
Schöneberg
chosen
Schöneberg is a district of Berlin, Germany, historically notable as the site of John F. Kennedy’s famous “Ich bin ein Berliner” speech.
-
B.
Reinickendorf
Reinickendorf is a borough in the northwest of Berlin, Germany, known for its mix of residential neighborhoods, industrial areas, and green spaces including parts of Lake Tegel.
-
C.
Starnberg
Starnberg is a lakeside town in Bavaria, Germany, known for its affluent residential character and scenic location on Lake Starnberg southwest of Munich.
-
D.
Steglitz-Zehlendorf
Steglitz-Zehlendorf is a borough in southwestern Berlin known for its affluent residential areas, lakes and forests, and historically significant sites such as the Wannsee Conference villa.
-
E.
Boblingen
Böblingen is a town in the German state of Baden-Württemberg, known for its automotive industry presence and proximity to Stuttgart.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25cee6f208190b996be4faa700910 |
completed | Feb. 28, 2026, 3:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3faf665a08190a9ce9fecfd057eae |
completed | March 1, 2026, 8:38 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.