Triple

T3061612
Position Surface form Disambiguated ID Type / Status
Subject Patria E62007 entity
Predicate hasSubsidiary P254 FINISHED
Object Patria Systems E62006 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: Patria Systems | Statement: [Patria, hasSubsidiary, Patria Systems]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Patria Systems
Context triple: [Patria, hasSubsidiary, Patria Systems]
  • A. Indra Sistemas
    Indra Sistemas is a Spanish multinational technology and defense company specializing in information technology, simulation, and advanced electronic systems for civil and military applications.
  • B. Nexter Systems
    Nexter Systems is a French defense company specializing in the design and manufacture of military land systems, including armored vehicles, artillery, and ammunition.
  • C. Santa Bárbara Sistemas
    Santa Bárbara Sistemas is a Spanish defense contractor known for designing and producing armored vehicles and other military equipment.
  • D. Patria Land Systems chosen
    Patria Land Systems is a Finnish defense company specializing in the design and production of armored military vehicles and related land warfare systems.
  • E. Unisys
    Unisys is an American global information technology company known for providing IT services, software, and infrastructure solutions to government and commercial clients.
  • 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_69ad85793e5c8190a358049bc4a98d8c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ad9e9f33d88190bd481cb7f18ceb91 completed March 8, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1ef0e757481908eb1d9693474c49d completed March 11, 2026, 10:39 p.m.
Created at: March 8, 2026, 3:02 p.m.