Triple

T9569493
Position Surface form Disambiguated ID Type / Status
Subject Gate of Rhegion E230877 entity
Predicate namedAfter P63 FINISHED
Object Rhegion E51793 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: Rhegion | Statement: [Gate of Rhegion, namedAfter, Rhegion]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rhegion
Context triple: [Gate of Rhegion, namedAfter, Rhegion]
  • A. Rhegion chosen
    Rhegion was an important ancient Greek city located at the southern tip of Italy, strategically positioned on the Strait of Messina.
  • B. Landes
    Landes is a department in southwestern France known for its vast Atlantic coastline, extensive pine forests, and popular surfing beaches.
  • C. Altmark region
    The Altmark region is a historic rural area in northern Germany known as one of the cradles of Brandenburg and Prussian history.
  • D. Biltine Region
    Biltine Region was a former administrative region in eastern Chad that was later reorganized and renamed Wadi Fira.
  • E. 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.
  • 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_69ca847f22188190a56e4a97625bef22 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd998940c881909f9025512cf72fe9 completed April 1, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69d152b5b40c81909a84e34a944abfd0 completed April 4, 2026, 6:04 p.m.
Created at: March 30, 2026, 8:04 p.m.