Triple

T21832937
Position Surface form Disambiguated ID Type / Status
Subject Monte Rosa–Dom chain E539044 entity
Predicate contains P35 FINISHED
Object Signalkuppe NE NERFINISHED

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: Signalkuppe | Statement: [Monte Rosa–Dom chain, contains, Signalkuppe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Signalkuppe
Context triple: [Monte Rosa–Dom chain, contains, Signalkuppe]
  • A. Signalkuppe chosen
    Signalkuppe is a prominent peak in the Pennine Alps on the border between Italy and Switzerland, known for hosting the high-altitude Capanna Regina Margherita hut near its summit.
  • B. Bärenkopf
    Bärenkopf is a mountain peak in the Austrian Alps that forms part of the Glockner Group.
  • C. Thalgauberg
    Thalgauberg is a small locality within the municipality of Thalgau in the Austrian state of Salzburg, known for its rural setting in the Alpine foothills.
  • D. Schneidhain
    Schneidhain is a district of the town Königstein im Taunus in the Hochtaunus region of Hesse, Germany.
  • E. Brocken
    Brocken is a prominent mountain in central Germany’s Harz range, known for its harsh climate, folklore, and role in literature and cultural history.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c475cda88190987d08f23caebdc1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f0a7a4d2d0819088ded045caeab52d completed April 28, 2026, 12:27 p.m.
Created at: April 16, 2026, 6:55 p.m.