Triple
T20788972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Block VII |
E511718
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object |
town of Binz
The town of Binz is a popular seaside resort on Germany’s Baltic Sea island of Rügen, known for its sandy beaches and historic resort architecture.
|
E1450699
|
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: town of Binz | Statement: [Block VII, locatedNear, town of Binz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: town of Binz Context triple: [Block VII, locatedNear, town of Binz]
-
A.
town of Lübz
The town of Lübz is a small historic municipality in the German state of Mecklenburg-Vorpommern, known for its traditional architecture and regional brewery.
-
B.
Bendorf
Bendorf is a town on the Rhine River in Rhineland-Palatinate, Germany, known for its industrial heritage and proximity to Koblenz.
-
C.
Bissingen
Bissingen is a suburb of the town of Herbrechtingen in the state of Baden-Württemberg, Germany.
-
D.
Bissingen
Bissingen is a municipality in the Donau-Ries district of Bavaria in southern Germany, known for its rural character and location near the Swabian Jura.
-
E.
Inzlingen
Inzlingen is a small municipality in the district of Lörrach in the state of Baden-Württemberg in southwestern Germany, near the Swiss border.
- 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: town of Binz Triple: [Block VII, locatedNear, town of Binz]
Generated description
The town of Binz is a popular seaside resort on Germany’s Baltic Sea island of Rügen, known for its sandy beaches and historic resort architecture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: town of Binz Target entity description: The town of Binz is a popular seaside resort on Germany’s Baltic Sea island of Rügen, known for its sandy beaches and historic resort architecture.
-
A.
town of Lübz
The town of Lübz is a small historic municipality in the German state of Mecklenburg-Vorpommern, known for its traditional architecture and regional brewery.
-
B.
Bendorf
Bendorf is a town on the Rhine River in Rhineland-Palatinate, Germany, known for its industrial heritage and proximity to Koblenz.
-
C.
Bissingen
Bissingen is a suburb of the town of Herbrechtingen in the state of Baden-Württemberg, Germany.
-
D.
Bissingen
Bissingen is a municipality in the Donau-Ries district of Bavaria in southern Germany, known for its rural character and location near the Swabian Jura.
-
E.
Inzlingen
Inzlingen is a small municipality in the district of Lörrach in the state of Baden-Württemberg in southwestern Germany, near the Swiss border.
- 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_69e0b4cb83948190bd57bec21d78ed53 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c28dfb8c8190a10289c157a61c67 |
completed | April 21, 2026, 12:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08f8ba7c00819083aa29efa82ad4aa |
completed | May 16, 2026, 11:07 p.m. |
| NEDg | Description generation | batch_6a08f9588b7081908c0fad68c9a845dc |
completed | May 16, 2026, 11:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08f9e50c6481908be5a61dab994012 |
completed | May 16, 2026, 11:12 p.m. |
Created at: April 16, 2026, 12:38 p.m.