Triple
T10603308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bansin |
E275805
|
entity |
| Predicate | nearbyPlace |
P2064
|
FINISHED |
| Object | Heringsdorf |
E308284
|
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: Heringsdorf | Statement: [Bansin, nearbyPlace, Heringsdorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heringsdorf Context triple: [Bansin, nearbyPlace, Heringsdorf]
-
A.
Heringsdorf
chosen
Heringsdorf is a seaside resort town on the Baltic Sea coast of the island of Usedom in northeastern Germany, known for its historic pier and spa architecture.
-
B.
Hennigsdorf
Hennigsdorf is a town in the German state of Brandenburg, located just northwest of Berlin and known for its industrial heritage and proximity to the Havel River.
-
C.
Heinersdorf
Heinersdorf is a residential locality in the borough of Pankow in Berlin, Germany, known for its suburban character and proximity to the city center.
-
D.
Augustdorf
Augustdorf is a municipality in North Rhine-Westphalia, Germany, known for its proximity to the Teutoburg Forest and its significant military presence, including Bundeswehr facilities.
-
E.
Hermsdorf
Hermsdorf is a small town in the German state of Thuringia, known as an industrial and transport hub near the city of Jena.
- 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_69d6aaf948d88190806cc3a8c47a3fb2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d6ded6d698819084f96f46ea941461 |
completed | April 8, 2026, 11:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de552d2d548190b6ade494ef2cbe7e |
completed | April 14, 2026, 2:54 p.m. |
Created at: April 8, 2026, 7:32 p.m.