Triple

T18396417
Position Surface form Disambiguated ID Type / Status
Subject Tyrol E449881 entity
Predicate containsCity P294 FINISHED
Object Lienz 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: Lienz | Statement: [Tyrol, containsCity, Lienz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lienz
Context triple: [Tyrol, containsCity, Lienz]
  • A. Lienz chosen
    Lienz is a small alpine town in East Tyrol, Austria, known for its picturesque mountain scenery and role as a regional cultural and economic center.
  • B. Ischl
    The Ischl is a river in Upper Austria that flows through the spa town of Bad Ischl before joining the Traun.
  • C. Lustenau
    Lustenau is a large market town in the Austrian state of Vorarlberg, known for its location on the Rhine near the Swiss border and its strong textile industry heritage.
  • D. Wörgl
    Wörgl is a small Austrian town in the state of Tyrol, known for its role in early 20th-century economic experiments with local currency and its location in the Inn Valley near major Alpine ski areas.
  • E. Bludenz
    Bludenz is a small alpine town in western Austria known as a regional hub for skiing, hiking, and chocolate production.
  • 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_69d8b9fab8a8819086a9ddc0871715e0 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e51846bb4c8190990f42a792a78ee0 completed April 19, 2026, 6 p.m.
Created at: April 10, 2026, 10:46 a.m.