Triple
T16480611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grünhornlücke |
E400305
|
entity |
| Predicate | nameElement |
P27866
|
FINISHED |
| Object | Grünhorn |
E1214463
|
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: Grünhorn | Statement: [Grünhornlücke, nameElement, Grünhorn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grünhorn Context triple: [Grünhornlücke, nameElement, Grünhorn]
-
A.
Grünhorn
chosen
Grünhorn is a prominent peak in the Bernese Alps of Switzerland, known for its glaciated slopes and alpine climbing routes.
-
B.
Hornschuch
Hornschuch is a German surname most notably associated with Karl Georg Hornschuch, a 19th-century botanist and bryologist.
-
C.
Hornig
Hornig is a surname most notably associated with Donald F. Hornig, an American chemist and presidential science advisor involved in the Manhattan Project.
-
D.
Harpe
Harpe is a figure in Greek mythology known primarily as the mother of Oenomaus, the king of Pisa in Elis.
-
E.
Harpe
Harpe is a German surname most notably borne by Wehrmacht general Josef Harpe during World War II.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e01f6c88190b75a0d6c94786426 |
completed | April 18, 2026, 7:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00581ebe888190a331974473f1be1a |
completed | May 10, 2026, 10:04 a.m. |
Created at: April 10, 2026, 5:13 a.m.