Triple
T16480591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grünhornlücke |
E400305
|
entity |
| Predicate | between |
P1262
|
FINISHED |
| Object | Fiescherhörner |
E1214460
|
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: Fiescherhörner | Statement: [Grünhornlücke, between, Fiescherhörner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fiescherhörner Context triple: [Grünhornlücke, between, Fiescherhörner]
-
A.
Fiescherhörner
chosen
Fiescherhörner is a group of prominent high Alpine peaks in the Bernese Alps of Switzerland, known for their glaciated summits and challenging mountaineering routes.
-
B.
Hornig
Hornig is a surname most notably associated with Donald F. Hornig, an American chemist and presidential science advisor involved in the Manhattan Project.
-
C.
Hornschuch
Hornschuch is a German surname most notably associated with Karl Georg Hornschuch, a 19th-century botanist and bryologist.
-
D.
Horns
Horns is a dark fantasy-horror novel by Joe Hill that follows a man who mysteriously grows devilish horns and gains disturbing supernatural powers after being accused of his girlfriend’s murder.
-
E.
Grünhorn
Grünhorn is a prominent peak in the Bernese Alps of Switzerland, known for its glaciated slopes and alpine climbing routes.
- 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.