Triple
T10923512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Constance region |
E258004
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Meersburg
Meersburg is a historic town in southern Germany known for its medieval castle, picturesque old town, and scenic location on the shores of Lake Constance.
|
E897713
|
NE FINISHED |
How this triple was built (4 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: Meersburg | Statement: [Lake Constance region, contains, Meersburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meersburg Context triple: [Lake Constance region, contains, Meersburg]
-
A.
Speyer
Speyer is a historic city in southwestern Germany on the Rhine River, renowned for its Romanesque imperial cathedral, a UNESCO World Heritage Site.
-
B.
Spassburg
Spassburg is the German-themed area of the Six Flags Fiesta Texas amusement park, featuring rides, shops, and architecture inspired by traditional German towns.
-
C.
Müggelheim
Müggelheim is a village-like district in the southeastern part of Berlin, Germany, characterized by its forests, lakes, and tranquil, semi-rural atmosphere.
-
D.
Landsberg
Landsberg is a town in the Saalekreis district of the German state of Saxony-Anhalt.
-
E.
Trier
Trier is a historic city in western Germany, renowned as one of the country’s oldest cities with extensive Roman ruins and medieval landmarks.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Meersburg Triple: [Lake Constance region, contains, Meersburg]
Generated description
Meersburg is a historic town in southern Germany known for its medieval castle, picturesque old town, and scenic location on the shores of Lake Constance.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Meersburg Target entity description: Meersburg is a historic town in southern Germany known for its medieval castle, picturesque old town, and scenic location on the shores of Lake Constance.
-
A.
Speyer
Speyer is a historic city in southwestern Germany on the Rhine River, renowned for its Romanesque imperial cathedral, a UNESCO World Heritage Site.
-
B.
Spassburg
Spassburg is the German-themed area of the Six Flags Fiesta Texas amusement park, featuring rides, shops, and architecture inspired by traditional German towns.
-
C.
Müggelheim
Müggelheim is a village-like district in the southeastern part of Berlin, Germany, characterized by its forests, lakes, and tranquil, semi-rural atmosphere.
-
D.
Landsberg
Landsberg is a town in the Saalekreis district of the German state of Saxony-Anhalt.
-
E.
Trier
Trier is a historic city in western Germany, renowned as one of the country’s oldest cities with extensive Roman ruins and medieval landmarks.
- F. None of above. chosen
Provenance (5 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_69d6aa864ed88190818280ab6791d065 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7708e3fd881908da10f24a856364c |
completed | April 9, 2026, 9:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e34455ea4c8190b6f2433f3f745b76 |
completed | April 18, 2026, 8:44 a.m. |
| NEDg | Description generation | batch_69e3556ad7ec819095b3babc67ecdfd4 |
completed | April 18, 2026, 9:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e358f860f08190bfd10519ff3806aa |
completed | April 18, 2026, 10:12 a.m. |
Created at: April 8, 2026, 9:22 p.m.