Triple
T624256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harz |
E14581
|
entity |
| Predicate | highestPoint |
P210
|
FINISHED |
| Object |
Brocken
Brocken is a prominent mountain in central Germany’s Harz range, known for its harsh climate, folklore, and role in literature and cultural history.
|
E79319
|
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: Brocken | Statement: [Harz, highestPoint, Brocken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brocken Context triple: [Harz, highestPoint, Brocken]
-
A.
Zugspitze
Zugspitze is the highest mountain in Germany, located in the Bavarian Alps near the Austrian border.
-
B.
Zumsteinspitze
Zumsteinspitze is one of the high summits of the Monte Rosa massif in the Pennine Alps on the border between Switzerland and Italy.
-
C.
Erzhausen
Erzhausen is a small municipality in the state of Hesse in central Germany, located near Darmstadt and part of the Rhine-Main metropolitan region.
-
D.
Ai-Petri Mountain
Ai-Petri Mountain is a striking peak in Crimea’s Crimean Mountains, famous for its jagged cliffs, panoramic views over the Black Sea coast, and popular cable car access from nearby resort towns.
-
E.
Hallbergmoos
Hallbergmoos is a municipality in Bavaria, Germany, known for hosting major aerospace and technology companies near Munich.
- 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: Brocken Triple: [Harz, highestPoint, Brocken]
Generated description
Brocken is a prominent mountain in central Germany’s Harz range, known for its harsh climate, folklore, and role in literature and cultural history.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brocken Target entity description: Brocken is a prominent mountain in central Germany’s Harz range, known for its harsh climate, folklore, and role in literature and cultural history.
-
A.
Zugspitze
Zugspitze is the highest mountain in Germany, located in the Bavarian Alps near the Austrian border.
-
B.
Zumsteinspitze
Zumsteinspitze is one of the high summits of the Monte Rosa massif in the Pennine Alps on the border between Switzerland and Italy.
-
C.
Erzhausen
Erzhausen is a small municipality in the state of Hesse in central Germany, located near Darmstadt and part of the Rhine-Main metropolitan region.
-
D.
Ai-Petri Mountain
Ai-Petri Mountain is a striking peak in Crimea’s Crimean Mountains, famous for its jagged cliffs, panoramic views over the Black Sea coast, and popular cable car access from nearby resort towns.
-
E.
Hallbergmoos
Hallbergmoos is a municipality in Bavaria, Germany, known for hosting major aerospace and technology companies near Munich.
- 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_69a4934b17c881909ace8270e8ddd202 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e43002c81908e0c7dab29b75978 |
completed | March 1, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a56c4b64088190a033462dd923f5b2 |
completed | March 2, 2026, 10:54 a.m. |
| NEDg | Description generation | batch_69a56d4af33081908c3c5649003e86e4 |
completed | March 2, 2026, 10:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a56dd4bb808190a5562a5f8bcf2910 |
completed | March 2, 2026, 11 a.m. |
Created at: March 1, 2026, 7:35 p.m.