Triple

T8200690
Position Surface form Disambiguated ID Type / Status
Subject Linn E191563 entity
Predicate hasPart P35 FINISHED
Object Altstadt Linn E718606 NE FINISHED

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: Altstadt Linn | Statement: [Linn, hasPart, Altstadt Linn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Altstadt Linn
Context triple: [Linn, hasPart, Altstadt Linn]
  • A. Altstadt Linn chosen
    Altstadt Linn is the historic old town district of Linn, known for its well-preserved medieval architecture and traditional urban layout.
  • B. Bergneustadt
    Bergneustadt is a small town in North Rhine-Westphalia, Germany, known for its location in the hilly Oberbergischer Kreis region and its traditional half-timbered architecture.
  • C. Lobethal
    Lobethal is a small town in South Australia known for its German heritage and popular annual Christmas lights festival.
  • D. Eulachstadt
    Eulachstadt is a nickname for the Swiss city of Winterthur, reflecting its historical association with the Eulach River and its development as an important industrial and cultural center.
  • E. City of Owosso
    The City of Owosso is a small industrial and residential community in central Michigan known historically for manufacturing and its preserved steam railroad attractions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca82c6e9548190a4c5ca14516e4417 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb5df6e7548190846a1afd62ec6d0a completed March 31, 2026, 5:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd34a9c8f08190a8a79b7baa7ffded completed April 1, 2026, 3:07 p.m.
Created at: March 30, 2026, 5:43 p.m.