Triple

T15471619
Position Surface form Disambiguated ID Type / Status
Subject Dura-Europos E376673 entity
Predicate originalName P65 FINISHED
Object Europos E597571 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: Europos | Statement: [Dura-Europos, originalName, Europos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Europos
Context triple: [Dura-Europos, originalName, Europos]
  • A. Europos
    Europos is an ancient city historically known as Rayy (or Rey), located near modern-day Tehran in Iran and recognized as one of the oldest continuously inhabited settlements in the region.
  • B. Europos chosen
    Europos was an ancient Macedonian town traditionally identified as the birthplace of the Seleucid Empire’s founder, Seleucus I Nicator.
  • C. De Europa
    De Europa is a 15th-century humanist treatise by Pope Pius II that offers one of the earliest comprehensive Renaissance descriptions of the geography, politics, and peoples of Europe.
  • D. Eura
    Eura is a municipality in southwestern Finland known for its rich archaeological heritage and prehistoric sites.
  • E. Europa
    Europa is a 1991 surreal, noir-style drama film by Danish director Lars von Trier, known for its striking visual style and hypnotic narrative set in post-World War II Germany.
  • 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_69d85cd21dcc81908646251b1c26ea00 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f6c57308190b4cfe661c26addd4 completed April 16, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2d0543f881909dfbbc77f2a96a1a completed May 9, 2026, 12:48 p.m.
Created at: April 10, 2026, 3:33 a.m.