Triple

T19176851
Position Surface form Disambiguated ID Type / Status
Subject Schönbuch region E469460 entity
Predicate hasNearbyCity P350 FINISHED
Object Reutlingen 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: Reutlingen | Statement: [Schönbuch region, hasNearbyCity, Reutlingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Reutlingen
Context triple: [Schönbuch region, hasNearbyCity, Reutlingen]
  • A. Reutlingen chosen
    Reutlingen is a city in southwestern Germany known for its location at the foot of the Swabian Jura and its well-preserved medieval old town.
  • B. Tuttlingen
    Tuttlingen is a town in the state of Baden-Württemberg in southern Germany, known as a major center of the medical technology and surgical instrument industry.
  • C. Rottweil
    Rottweil is a historic town in southwestern Germany known for its medieval architecture and as the namesake of the Rottweiler dog breed.
  • D. Pforzheim
    Pforzheim is a city in southwestern Germany, historically known for its jewelry and watchmaking industry and its heavy destruction during World War II.
  • E. Schwäbisch Gmünd
    Schwäbisch Gmünd is a historic town in the German state of Baden-Württemberg, known for its medieval architecture and long tradition of metalworking and jewelry craftsmanship.
  • 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_69d8dd09d5a081909ae43c286651ae5a completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5f618f18c8190b98995fda4b6fea0 completed April 20, 2026, 9:47 a.m.
Created at: April 10, 2026, 12:07 p.m.