Triple

T2164467
Position Surface form Disambiguated ID Type / Status
Subject Marburg, Hesse, Germany E46876 entity
Predicate twinTown P1072 FINISHED
Object Poitiers, France E72193 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: Poitiers, France | Statement: [Marburg, Hesse, Germany, twinTown, Poitiers, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Poitiers, France
Context triple: [Marburg, Hesse, Germany, twinTown, Poitiers, France]
  • A. Poitiers chosen
    Poitiers is a historic city in western France known for its Romanesque architecture, medieval heritage, and role as a regional center in the Nouvelle-Aquitaine region.
  • B. Bourges, France
    Bourges, France is a historic city in central France known for its well-preserved medieval architecture and the UNESCO-listed Bourges Cathedral.
  • C. Amiens, France
    Amiens, France is a historic city in northern France known for its Gothic cathedral and as the birthplace of French President Emmanuel Macron.
  • D. Montlouis-sur-Loire, France
    Montlouis-sur-Loire is a commune in central France’s Loire Valley, known for its vineyards and historic châteaux along the Loire River.
  • E. Montpellier, France
    Montpellier, France is a historic and vibrant city in southern France near the Mediterranean coast, known for its medieval architecture, large student population, and role as a regional cultural and economic center.
  • 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_69a88a184cbc8190877791f6552c2484 completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abbe8e1cfc81908adc0357ddfec701 completed March 7, 2026, 5:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae58ee18ac81909f02e2c87000365b completed March 9, 2026, 5:21 a.m.
Created at: March 4, 2026, 7:45 p.m.