Triple

T11843520
Position Surface form Disambiguated ID Type / Status
Subject Eurodistrict SaarMoselle E281713 entity
Predicate hasBorderCity P15361 FINISHED
Object Saarbrücken E269297 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: Saarbrücken | Statement: [Eurodistrict SaarMoselle, hasBorderCity, Saarbrücken]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saarbrücken
Context triple: [Eurodistrict SaarMoselle, hasBorderCity, Saarbrücken]
  • A. Saarbrücken chosen
    Saarbrücken is a German city on the Saar River known as an industrial, cultural, and educational center near the French border.
  • B. Saarlouis
    Saarlouis is a town in the German state of Saarland, known historically as a fortified city founded by Louis XIV of France near the French border.
  • C. Nassau-Saarbrücken
    Nassau-Saarbrücken was a small German principality of the House of Nassau located in the Saar region, historically notable for its role within the fragmented political landscape of the Holy Roman Empire.
  • D. Wissembourg
    Wissembourg is a historic town in northeastern France’s Alsace region, known for its well-preserved medieval architecture and proximity to the German border.
  • E. Kaiserslautern
    Kaiserslautern is a city in southwestern Germany known for its historic old town, technical university, and prominent football club 1. FC Kaiserslautern.
  • 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_69d6ab287ba48190a5178779fd19b9b7 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a65a597c8190b09f57463b279afc completed April 10, 2026, 7:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69f6a52fcfa081909cc312a56bf12693 completed May 3, 2026, 1:30 a.m.
Created at: April 8, 2026, 9:43 p.m.