Triple

T1027025
Position Surface form Disambiguated ID Type / Status
Subject Eurodistrict Strasbourg-Ortenau E22161 entity
Predicate hasMember P10 FINISHED
Object Achern
Achern is a small German town in the state of Baden-Württemberg, located near the Black Forest and close to the French border in the Upper Rhine region.
E122866 NE FINISHED

How this triple was built (4 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: Achern | Statement: [Eurodistrict Strasbourg-Ortenau, hasMember, Achern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Achern
Context triple: [Eurodistrict Strasbourg-Ortenau, hasMember, Achern]
  • A. Unterwallenstadt
    Unterwallenstadt is a small locality that forms part of the town of Lichtenfels in the Upper Franconia region of Bavaria, Germany.
  • B. Brigach
    Brigach is a river in Germany that forms one of the two headstreams of the Danube.
  • C. Lommersweiler
    Lommersweiler is a village and municipal section of the town of St. Vith in the German-speaking Community of eastern Belgium.
  • D. Aarau
    Aarau is a historic Swiss town and the capital of the canton of Aargau, known for its well-preserved old town and location near the Aare River.
  • E. Boblingen
    Böblingen is a town in the German state of Baden-Württemberg, known for its automotive industry presence and proximity to Stuttgart.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Achern
Triple: [Eurodistrict Strasbourg-Ortenau, hasMember, Achern]
Generated description
Achern is a small German town in the state of Baden-Württemberg, located near the Black Forest and close to the French border in the Upper Rhine region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Achern
Target entity description: Achern is a small German town in the state of Baden-Württemberg, located near the Black Forest and close to the French border in the Upper Rhine region.
  • A. Unterwallenstadt
    Unterwallenstadt is a small locality that forms part of the town of Lichtenfels in the Upper Franconia region of Bavaria, Germany.
  • B. Brigach
    Brigach is a river in Germany that forms one of the two headstreams of the Danube.
  • C. Lommersweiler
    Lommersweiler is a village and municipal section of the town of St. Vith in the German-speaking Community of eastern Belgium.
  • D. Aarau
    Aarau is a historic Swiss town and the capital of the canton of Aargau, known for its well-preserved old town and location near the Aare River.
  • E. Boblingen
    Böblingen is a town in the German state of Baden-Württemberg, known for its automotive industry presence and proximity to Stuttgart.
  • F. None of above. chosen

Provenance (5 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_69a493d6e380819097b384986ffc315c completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b7f6ff048190863f9c38162d09b7 completed March 1, 2026, 10:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac429675bc8190b2467ac86c41c3b5 completed March 7, 2026, 3:21 p.m.
NEDg Description generation batch_69ac430384ec8190a307c895bb12a122 completed March 7, 2026, 3:23 p.m.
NED2 Entity disambiguation (via description) batch_69ac437b62bc8190abfb721c570b4768 completed March 7, 2026, 3:25 p.m.
Created at: March 1, 2026, 7:41 p.m.