Triple
T15049449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wurmberg |
E379315
|
entity |
| Predicate | hasViewOf |
P854
|
FINISHED |
| Object | Brocken |
E79319
|
NE FINISHED |
How this triple was built (2 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: [Wurmberg, hasViewOf, Brocken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brocken Context triple: [Wurmberg, hasViewOf, Brocken]
-
A.
Brocken
chosen
Brocken is a prominent mountain in central Germany’s Harz range, known for its harsh climate, folklore, and role in literature and cultural history.
-
B.
Bärenkopf
Bärenkopf is a mountain peak in the Austrian Alps that forms part of the Glockner Group.
-
C.
Teufelstättkopf
Teufelstättkopf is a mountain peak in the Bavarian Ammergau Alps, popular with hikers for its scenic views and relatively accessible trails.
-
D.
Spittelberg
Spittelberg is a historic, village-like quarter in Vienna known for its preserved Biedermeier architecture, narrow cobblestone streets, and popular Christmas market.
-
E.
Kofel
Kofel is a distinctive, steep limestone peak overlooking the town of Oberammergau in the Ammergau Alps of Bavaria, Germany, popular with hikers and climbers.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69feae0da8008190a39d63648228a34c |
completed | May 9, 2026, 3:46 a.m. |
Created at: April 10, 2026, 3 a.m.