Triple

T11065107
Position Surface form Disambiguated ID Type / Status
Subject Legio X Gemina E261602 entity
Predicate garrison P75 FINISHED
Object Nijmegen E13123 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: Nijmegen | Statement: [Legio X Gemina, garrison, Nijmegen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nijmegen
Context triple: [Legio X Gemina, garrison, Nijmegen]
  • A. Nijmegen chosen
    Nijmegen is a historic Dutch city near the German border that played a crucial strategic role during World War II, particularly in the Allied advance in 1944.
  • B. Utrecht
    Utrecht is a historic city and province in the central Netherlands, known for its medieval old town, canals, and role as a religious and cultural center.
  • C. Utrecht
    Utrecht is a small town in South Africa’s KwaZulu-Natal province, known for its scenic surroundings and historical significance dating back to the 19th century.
  • D. Tilburg
    Tilburg is a city in the southern Netherlands known historically as an industrial and textile center and now as a regional cultural and educational hub.
  • E. Eindhoven
    Eindhoven is a major city in the southern Netherlands known for its industrial and technological significance, particularly as a hub for electronics and design.
  • 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_69d6aa98650481908609c7c56bfa7902 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d798edcab881909da1ba0394020ef8 completed April 9, 2026, 12:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff3643a23481909103166abb6aaa4e completed May 9, 2026, 1:27 p.m.
Created at: April 8, 2026, 9:26 p.m.