Triple

T126424
Position Surface form Disambiguated ID Type / Status
Subject Vulgar Latin E2560 entity
Predicate region P40 FINISHED
Object Dacia E8777 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: Dacia | Statement: [Vulgar Latin, region, Dacia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dacia
Context triple: [Vulgar Latin, region, Dacia]
  • A. Romania chosen
    Romania is a southeastern European country known for its role in World War II, its Carpathian mountain landscapes, and its historical regions such as Transylvania.
  • B. Hungary
    Hungary is a landlocked Central European country known for its rich history, distinct language (Hungarian), and capital city Budapest, famed for its thermal baths and architecture.
  • C. Bulgaria
    Bulgaria is a Southeast European country on the Balkan Peninsula, known for its rich historical heritage, diverse landscapes, and role as a member of the European Union and NATO.
  • D. Vichy
    Vichy is a spa town in central France renowned for its thermal springs, health resorts, and role as the seat of the World War II Vichy regime.
  • E. Austria
    Austria is a landlocked Central European country known for its Alpine landscapes, rich cultural and musical heritage, and status as a prosperous, democratic member of the European Union.
  • 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_69a251b54ea88190b18281669f59b4c0 completed Feb. 28, 2026, 2:23 a.m.
NER Named-entity recognition batch_69a25761e9248190a7205bfc36cb5c45 completed Feb. 28, 2026, 2:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69a29e4aeab48190bf2d140956278a42 completed Feb. 28, 2026, 7:50 a.m.
Created at: Feb. 28, 2026, 2:27 a.m.