Triple

T9093964
Position Surface form Disambiguated ID Type / Status
Subject Pratteln E217965 entity
Predicate hasTwinTown P919 FINISHED
Object Ettlingen E512308 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: Ettlingen | Statement: [Pratteln, hasTwinTown, Ettlingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ettlingen
Context triple: [Pratteln, hasTwinTown, Ettlingen]
  • A. Ettlingen chosen
    Ettlingen is a historic town in the state of Baden-Württemberg in southwestern Germany, known for its well-preserved old town and proximity to the city of Karlsruhe.
  • 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. Wiesloch
    Wiesloch is a town in the Rhine-Neckar district of Baden-Württemberg, Germany, known for its historical center and role as a regional commercial hub.
  • D. Blaubeuren
    Blaubeuren is a historic town in the Alb-Donau district of Baden-Württemberg, Germany, known for its medieval old town and the karst spring Blautopf.
  • E. Ebingen
    Ebingen is a district of Albstadt in the Swabian Jura region of Baden-Württemberg, Germany, historically known as an independent town and the birthplace of former German Chancellor Kurt Georg Kiesinger.
  • 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_69ca83d8ab5881909d8fddae363b32b1 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc96b347d4819085b33d0e20834f47 completed April 1, 2026, 3:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1c3f31db48190a63d0d60f108496f completed April 5, 2026, 2:07 a.m.
Created at: March 30, 2026, 7:14 p.m.