Triple
T12749835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warnemünde Lighthouse |
E304700
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Warnemünde |
E330763
|
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: Warnemünde | Statement: [Warnemünde Lighthouse, locatedIn, Warnemünde]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Warnemünde Context triple: [Warnemünde Lighthouse, locatedIn, Warnemünde]
-
A.
Warnemünde
chosen
Warnemünde is a seaside district and popular Baltic Sea resort of the German city of Rostock, known for its wide sandy beaches and maritime atmosphere.
-
B.
Ostseebad
Ostseebad is a German designation for a seaside resort town on the Baltic Sea, recognized for its coastal tourism and spa facilities.
-
C.
Rostock
Rostock is a historic Hanseatic city in northern Germany known for its significant seaport on the Baltic Sea and its long maritime and trading tradition.
-
D.
Stralsund
Stralsund is a historic Hanseatic port city on Germany’s Baltic Sea coast, known for its well-preserved medieval old town and brick Gothic architecture.
-
E.
Bandorf
Bandorf is a small district of the town of Remagen in the Rhineland-Palatinate region of western Germany.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96bd75f508190aaae0969f33d1523 |
completed | April 10, 2026, 9:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7941b62bc819082ddb1f48497ff3a |
completed | May 3, 2026, 6:29 p.m. |
Created at: April 9, 2026, 5:27 p.m.