Triple

T11790769
Position Surface form Disambiguated ID Type / Status
Subject Thionville railway station E280380 entity
Predicate serves P98 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: [Thionville railway station, serves, Thionville]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thionville
Context triple: [Thionville railway station, serves, 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_69d6ab258b808190b1735835c841e3a4 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a588d2c881909783c2d678c2a474 completed April 10, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f655515be48190a0793eef7b016852 completed May 2, 2026, 7:49 p.m.
Created at: April 8, 2026, 9:42 p.m.