Triple

T10540010
Position Surface form Disambiguated ID Type / Status
Subject Allgäu Alps E248669 entity
Predicate contains P35 FINISHED
Object Hoher Ifen
Hoher Ifen is a distinctive flat-topped mountain in the Allgäu Alps, known for its striking plateau summit and popular hiking and skiing routes.
E870961 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: Hoher Ifen | Statement: [Allgäu Alps, contains, Hoher Ifen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hoher Ifen
Context triple: [Allgäu Alps, contains, Hoher Ifen]
  • A. Hoche
    Hoche is a Paris Métro station located in the northeastern suburb of Pantin, serving as a stop on the city’s Line 5.
  • B. Mittelhorn
    Mittelhorn is a notable secondary summit in the Bernese Alps of Switzerland, forming part of the Wetterhorn massif.
  • C. Tennenlohe
    Tennenlohe is a district of Erlangen in Bavaria, Germany, known for its proximity to research institutions and the Tennenlohe Forest nature reserve.
  • D. Mount Wilis
    Mount Wilis is a solitary, inactive stratovolcano in East Java, Indonesia, known for its forested slopes and surrounding rural highland communities.
  • E. Moosrain
    Moosrain is a small locality or district that forms part of the Bavarian municipality of Gmund am Tegernsee in southern Germany.
  • 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: Hoher Ifen
Triple: [Allgäu Alps, contains, Hoher Ifen]
Generated description
Hoher Ifen is a distinctive flat-topped mountain in the Allgäu Alps, known for its striking plateau summit and popular hiking and skiing routes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hoher Ifen
Target entity description: Hoher Ifen is a distinctive flat-topped mountain in the Allgäu Alps, known for its striking plateau summit and popular hiking and skiing routes.
  • A. Hoche
    Hoche is a Paris Métro station located in the northeastern suburb of Pantin, serving as a stop on the city’s Line 5.
  • B. Mittelhorn
    Mittelhorn is a notable secondary summit in the Bernese Alps of Switzerland, forming part of the Wetterhorn massif.
  • C. Tennenlohe
    Tennenlohe is a district of Erlangen in Bavaria, Germany, known for its proximity to research institutions and the Tennenlohe Forest nature reserve.
  • D. Mount Wilis
    Mount Wilis is a solitary, inactive stratovolcano in East Java, Indonesia, known for its forested slopes and surrounding rural highland communities.
  • E. Moosrain
    Moosrain is a small locality or district that forms part of the Bavarian municipality of Gmund am Tegernsee in southern Germany.
  • 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_69d381c733c08190ab1dd6239f5f34ae completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d50a582be48190856c6f272eea4dcf completed April 7, 2026, 1:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69d9341d96c08190a6ba644b9acfe2c8 completed April 10, 2026, 5:32 p.m.
NEDg Description generation batch_69d93802a4488190aa86ae209650d4e7 completed April 10, 2026, 5:48 p.m.
NED2 Entity disambiguation (via description) batch_69d938fcc3c48190a4acaaf75c1aa304 completed April 10, 2026, 5:53 p.m.
Created at: April 6, 2026, 12:32 p.m.