Triple

T3108735
Position Surface form Disambiguated ID Type / Status
Subject Esch-sur-Alzette E64897 entity
Predicate hasTwinTown P919 FINISHED
Object Eschwege E241325 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: Eschwege | Statement: [Esch-sur-Alzette, hasTwinTown, Eschwege]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eschwege
Context triple: [Esch-sur-Alzette, hasTwinTown, Eschwege]
  • A. Eschwege chosen
    Eschwege is a small historic town in the German state of Hesse, known for its medieval architecture and location near the Werra River.
  • B. Weidach
    Weidach is a locality or district that forms part of the municipality of Blaustein in the state of Baden-Württemberg, Germany.
  • C. Oberweser
    Oberweser is the name given to the upper course of the Weser River in central Germany, encompassing its initial stretch after the confluence of its headstreams.
  • D. Saaleck
    Saaleck is a small locality in Germany, historically notable as the birthplace of the pioneering Protestant theologian Johann Salomo Semler.
  • E. Schwabach
    Schwabach is a historic town in northern Bavaria, Germany, known for its traditional gold-beating craft and well-preserved old town.
  • 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_69ad857eeaf48190b34ebfdaa7a264cf completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada29eacc88190a19c5ca8e53e3dca completed March 8, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b224c9ecd481909198bb0a6c0c31e8 completed March 12, 2026, 2:28 a.m.
Created at: March 8, 2026, 3:04 p.m.