Triple

T19431428
Position Surface form Disambiguated ID Type / Status
Subject Gare de Valenciennes E486121 entity
Predicate connectsTo P845 FINISHED
Object Thionville E58199 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: Thionville | Statement: [Gare de Valenciennes, connectsTo, Thionville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thionville
Context triple: [Gare de Valenciennes, connectsTo, Thionville]
  • A. Thionville chosen
    Thionville is a town in northeastern France near the Luxembourg border, known historically as a strategic industrial and military center in the Moselle region.
  • B. Bar-le-Duc
    Bar-le-Duc is a historic town in northeastern France, known as the former capital of the Duchy of Bar and for its Renaissance architecture and traditional mirabelle plum jam.
  • C. Bois-le-Duc
    Bois-le-Duc is the French name for ’s-Hertogenbosch, a historic Dutch city known for its medieval architecture and cultural heritage in the southern Netherlands.
  • D. Pont-à-Mousson
    Pont-à-Mousson is a historic town in northeastern France on the Moselle River, known for its medieval heritage and former university.
  • E. Sarreguemines
    Sarreguemines is a town in northeastern France near the German border, historically known for its ceramics and faience production.
  • 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_69d8e8d688f881909c85104a62e09d8a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6335b4e388190913ded15ad165b7b completed April 20, 2026, 2:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a074e693c7c8190b7c524bc31898379 completed May 15, 2026, 4:48 p.m.
Created at: April 10, 2026, 1:37 p.m.