Triple
T15049758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Innerste Dam |
E379328
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object |
Langelsheim
Langelsheim is a small town in Lower Saxony, Germany, situated in the Harz region and known for its scenic surroundings and historical mining heritage.
|
E1190920
|
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: Langelsheim | Statement: [Innerste Dam, locatedNear, Langelsheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Langelsheim Context triple: [Innerste Dam, locatedNear, Langelsheim]
-
A.
Langenau
Langenau is a small town in the Alb-Donau district of Baden-Württemberg in southern Germany, known for its historic center and proximity to the Swabian Jura.
-
B.
Langenberg
Langenberg is a prominent mountain in the Rothaargebirge range of Germany, known as the highest peak in the state of North Rhine-Westphalia.
-
C.
Hettstedt
Hettstedt is a small German town in the state of Saxony-Anhalt, historically known for its copper mining and metalworking industry.
-
D.
Griesheim
Griesheim is a town in the German state of Hesse, located near the city of Darmstadt and known for its residential character and local industry.
-
E.
Wilhelmsruh
Wilhelmsruh is a locality in the borough of Pankow in Berlin, Germany, known for its residential character and historical ties to Berlin’s former border zone.
- 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: Langelsheim Triple: [Innerste Dam, locatedNear, Langelsheim]
Generated description
Langelsheim is a small town in Lower Saxony, Germany, situated in the Harz region and known for its scenic surroundings and historical mining heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Langelsheim Target entity description: Langelsheim is a small town in Lower Saxony, Germany, situated in the Harz region and known for its scenic surroundings and historical mining heritage.
-
A.
Langenau
Langenau is a small town in the Alb-Donau district of Baden-Württemberg in southern Germany, known for its historic center and proximity to the Swabian Jura.
-
B.
Langenberg
Langenberg is a prominent mountain in the Rothaargebirge range of Germany, known as the highest peak in the state of North Rhine-Westphalia.
-
C.
Hettstedt
Hettstedt is a small German town in the state of Saxony-Anhalt, historically known for its copper mining and metalworking industry.
-
D.
Griesheim
Griesheim is a town in the German state of Hesse, located near the city of Darmstadt and known for its residential character and local industry.
-
E.
Wilhelmsruh
Wilhelmsruh is a locality in the borough of Pankow in Berlin, Germany, known for its residential character and historical ties to Berlin’s former border zone.
- 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_69d85cd64d108190853797a95c11cc45 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69deda8f71988190b4fe7f7de4ccb798 |
completed | April 15, 2026, 12:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbb7b1e48190b55c40e0cb837446 |
completed | May 10, 2026, 1:13 a.m. |
| NEDg | Description generation | batch_69ffdd527cfc8190a616a2334edffd02 |
completed | May 10, 2026, 1:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffdda1a0908190b7c880c5d66f7400 |
completed | May 10, 2026, 1:21 a.m. |
Created at: April 10, 2026, 3 a.m.