Triple

T19632807
Position Surface form Disambiguated ID Type / Status
Subject Gmunden E471312 entity
Predicate hasNearbyMountain P651 FINISHED
Object Traunstein 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: Traunstein | Statement: [Gmunden, hasNearbyMountain, Traunstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Traunstein
Context triple: [Gmunden, hasNearbyMountain, Traunstein]
  • A. Traunstein
    Traunstein is a town in southeastern Bavaria, Germany, known as a regional administrative and cultural center near the Chiemsee and the Alps.
  • B. Traunstein chosen
    Traunstein is a prominent limestone mountain in the Salzkammergut region of Upper Austria, overlooking Lake Traunsee and popular for hiking and climbing.
  • C. Rosenheim
    Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
  • D. Eichstätt
    Eichstätt is a historic Bavarian town in southern Germany known for its baroque architecture, Catholic university, and location within the Altmühltal Nature Park.
  • E. Straßkirchen
    Straßkirchen is a municipality in Lower Bavaria, Germany, known for its rural character and location near the city of Straubing.
  • 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_69d8e511f28481909f4bc3ea9191e54a completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e6410449ec8190b8c20c0e09cd9156 completed April 20, 2026, 3:06 p.m.
Created at: April 10, 2026, 1:44 p.m.