Triple

T14463244
Position Surface form Disambiguated ID Type / Status
Subject Regio IX E358638 entity
Predicate hasName P744 FINISHED
Object Regio nona E539899 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: Regio nona | Statement: [Regio IX, hasName, Regio nona]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Regio nona
Context triple: [Regio IX, hasName, Regio nona]
  • A. Regio
    Regio is a regional train service brand in Switzerland operated by the Swiss Federal Railways (SBB/CFF/FFS), providing local and stopping services between towns and cities.
  • B. Regio XIII Aventinus chosen
    Regio XIII Aventinus was one of the 14 administrative regions of ancient Rome, encompassing the Aventine Hill and its surrounding areas.
  • C. Sesto
    Sesto is a central operatic character in Handel’s “Giulio Cesare,” portrayed as a young Roman seeking to avenge his father’s death.
  • D. Tavullia
    Tavullia is a small Italian town in the Marche region, best known as the hometown of MotoGP legend Valentino Rossi.
  • E. Regio XI
    Regio XI was one of the administrative regions of ancient Rome, centered around the Circus Maximus and encompassing key entertainment and religious sites.
  • 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_69d82794dfa081909b9134ad2e32244b completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de91ad67bc81908ecdaa7262f6dc55 completed April 14, 2026, 7:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd64973dc08190ab893c95ea3f066c completed May 8, 2026, 4:20 a.m.
Created at: April 10, 2026, 1:19 a.m.