Triple
T10101332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Altenau |
E216207
|
entity |
| Predicate | locatedNear |
P294
|
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: [Altenau, locatedNear, Brocken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brocken Context triple: [Altenau, locatedNear, 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.
Berghaupten
Berghaupten is a small municipality in the Ortenau district of Baden-Württemberg in southwestern Germany, known for its scenic location in the Black Forest region.
-
D.
Schneidhain
Schneidhain is a district of the town Königstein im Taunus in the Hochtaunus region of Hesse, Germany.
-
E.
Faulhorn
Faulhorn is a mountain in the Bernese Alps of Switzerland, known for its panoramic views of surrounding peaks and lakes and for hosting one of the oldest mountain hotels in the Alps.
- 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_69ca83d039f08190b9d10363221c69fb |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd09878f88190bcfa2c81fb10e821 |
completed | April 2, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2cbf9ffb88190a87833d6fe080950 |
completed | April 5, 2026, 8:54 p.m. |
Created at: March 30, 2026, 9:02 p.m.