Triple
T11085678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samtgemeinde Elbtalaue |
E262113
|
entity |
| Predicate | containsAdministrativeTerritorialEntity |
P747
|
FINISHED |
| Object |
Göhrde
Göhrde is a municipality in Lower Saxony, Germany, known for its extensive forested areas and historical royal hunting grounds.
|
E913791
|
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: Göhrde | Statement: [Samtgemeinde Elbtalaue, containsAdministrativeTerritorialEntity, Göhrde]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Göhrde Context triple: [Samtgemeinde Elbtalaue, containsAdministrativeTerritorialEntity, Göhrde]
-
A.
Göhren
Göhren is a seaside resort town on the Baltic Sea coast of Germany, located on the island of Rügen and known for its beaches and tourism.
-
B.
Ehringshausen
Ehringshausen is a municipality in the Lahn-Dill district of the German state of Hesse.
-
C.
Gevelsberg
Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan region.
-
D.
Hettstedt
Hettstedt is a small German town in the state of Saxony-Anhalt, historically known for its copper mining and metalworking industry.
-
E.
Korbach
Korbach is a historic town in the German state of Hesse, known as the district seat of Waldeck-Frankenberg and for its well-preserved medieval old town.
- 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: Göhrde Triple: [Samtgemeinde Elbtalaue, containsAdministrativeTerritorialEntity, Göhrde]
Generated description
Göhrde is a municipality in Lower Saxony, Germany, known for its extensive forested areas and historical royal hunting grounds.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Göhrde Target entity description: Göhrde is a municipality in Lower Saxony, Germany, known for its extensive forested areas and historical royal hunting grounds.
-
A.
Göhren
Göhren is a seaside resort town on the Baltic Sea coast of Germany, located on the island of Rügen and known for its beaches and tourism.
-
B.
Ehringshausen
Ehringshausen is a municipality in the Lahn-Dill district of the German state of Hesse.
-
C.
Gevelsberg
Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan region.
-
D.
Hettstedt
Hettstedt is a small German town in the state of Saxony-Anhalt, historically known for its copper mining and metalworking industry.
-
E.
Korbach
Korbach is a historic town in the German state of Hesse, known as the district seat of Waldeck-Frankenberg and for its well-preserved medieval old town.
- 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_69d6aa9983c08190b0ef61603b69feac |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d799c2c7d4819087ac793153340178 |
completed | April 9, 2026, 12:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4cbfe70fc8190adf97e3ea7d06527 |
completed | April 19, 2026, 12:35 p.m. |
| NEDg | Description generation | batch_69e4d9e87508819080932fac06fb754d |
completed | April 19, 2026, 1:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4dda28b0081909245b65faae3533b |
completed | April 19, 2026, 1:50 p.m. |
Created at: April 8, 2026, 9:27 p.m.