Triple
T19565498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | district of Lörrach |
E489570
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Binzen
Binzen is a small municipality in the district of Lörrach in the state of Baden-Württemberg in southwestern Germany.
|
E1383165
|
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: Binzen | Statement: [district of Lörrach, containsMunicipality, Binzen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Binzen Context triple: [district of Lörrach, containsMunicipality, Binzen]
-
A.
Ogikubo
Ogikubo is a residential and commercial district in western Tokyo known for its relaxed atmosphere, ramen shops, and role as a transport hub on the Chūō Line.
-
B.
Nakanoshima
Nakanoshima is a central river island and business district in Osaka, Japan, known for its government buildings, cultural institutions, and scenic waterfront parks.
-
C.
Nakanoshima
Nakanoshima is a small Japanese island associated with Etajima in Hiroshima Prefecture, known for its coastal scenery and role within the local island group.
-
D.
Somero
Somero is a small town and municipality in southwestern Finland known for its rural landscapes and agricultural heritage.
-
E.
Kogarah
Kogarah is a suburb in southern Sydney, New South Wales, Australia, known as a residential and commercial hub in the St George area.
- 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: Binzen Triple: [district of Lörrach, containsMunicipality, Binzen]
Generated description
Binzen is a small municipality in the district of Lörrach in the state of Baden-Württemberg in southwestern Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Binzen Target entity description: Binzen is a small municipality in the district of Lörrach in the state of Baden-Württemberg in southwestern Germany.
-
A.
Ogikubo
Ogikubo is a residential and commercial district in western Tokyo known for its relaxed atmosphere, ramen shops, and role as a transport hub on the Chūō Line.
-
B.
Nakanoshima
Nakanoshima is a small Japanese island associated with Etajima in Hiroshima Prefecture, known for its coastal scenery and role within the local island group.
-
C.
Nakanoshima
Nakanoshima is a central river island and business district in Osaka, Japan, known for its government buildings, cultural institutions, and scenic waterfront parks.
-
D.
Somero
Somero is a small town and municipality in southwestern Finland known for its rural landscapes and agricultural heritage.
-
E.
Kogarah
Kogarah is a suburb in southern Sydney, New South Wales, Australia, known as a residential and commercial hub in the St George area.
- 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63f777cf081909312b46ac09bce7c |
completed | April 20, 2026, 3 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a075787d15c8190b680c74afa7b2220 |
completed | May 15, 2026, 5:27 p.m. |
| NEDg | Description generation | batch_6a0758aeffb081909c100c7509010d54 |
completed | May 15, 2026, 5:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07598fdd908190b3f999b61447f8d2 |
completed | May 15, 2026, 5:36 p.m. |
Created at: April 10, 2026, 1:42 p.m.