Triple

T16480590
Position Surface form Disambiguated ID Type / Status
Subject Grünhornlücke E400305 entity
Predicate between P1262 FINISHED
Object Grünhorn
Grünhorn is a prominent peak in the Bernese Alps of Switzerland, known for its glaciated slopes and alpine climbing routes.
 E1214463 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: Grünhorn | Statement: [Grünhornlücke, between, Grünhorn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Grünhorn
Context triple: [Grünhornlücke, between, Grünhorn]
  • A. Hornschuch
    Hornschuch is a German surname most notably associated with Karl Georg Hornschuch, a 19th-century botanist and bryologist.
  • 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. Harpe
    Harpe is a figure in Greek mythology known primarily as the mother of Oenomaus, the king of Pisa in Elis.
  • D. Harpe
    Harpe is a German surname most notably borne by Wehrmacht general Josef Harpe during World War II.
  • E. Hirschgeweih
    Hirschgeweih was the colloquial German nickname for the prominent, multi-dipole “stag’s antlers” antenna array used on the FuG 220 Lichtenstein SN-2 airborne radar in World War II.
  • 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: Grünhorn
Triple: [Grünhornlücke, between, Grünhorn]
Generated description
Grünhorn is a prominent peak in the Bernese Alps of Switzerland, known for its glaciated slopes and alpine climbing routes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Grünhorn
Target entity description: Grünhorn is a prominent peak in the Bernese Alps of Switzerland, known for its glaciated slopes and alpine climbing routes.
  • A. Hornschuch
    Hornschuch is a German surname most notably associated with Karl Georg Hornschuch, a 19th-century botanist and bryologist.
  • 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. Harpe
    Harpe is a figure in Greek mythology known primarily as the mother of Oenomaus, the king of Pisa in Elis.
  • D. Harpe
    Harpe is a German surname most notably borne by Wehrmacht general Josef Harpe during World War II.
  • E. Hirschgeweih
    Hirschgeweih was the colloquial German nickname for the prominent, multi-dipole “stag’s antlers” antenna array used on the FuG 220 Lichtenstein SN-2 airborne radar in World War II.
  • 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_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_6a004f61eca48190816fe1e3dbe6e901 completed May 10, 2026, 9:26 a.m.
NEDg Description generation batch_6a004ff9e2e88190afa4726e3ba71ea9 completed May 10, 2026, 9:29 a.m.
NED2 Entity disambiguation (via description) batch_6a00505beaa881909aca531af1149fbc completed May 10, 2026, 9:31 a.m.
Created at: April 10, 2026, 5:13 a.m.