Triple

T2603051
Position Surface form Disambiguated ID Type / Status
Subject Slough E58388 entity
Predicate hasTwinTown P919 FINISHED
Object Riga, Latvia E20805 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: Riga, Latvia | Statement: [Slough, hasTwinTown, Riga, Latvia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Riga, Latvia
Context triple: [Slough, hasTwinTown, Riga, Latvia]
  • A. Riga
    Riga is a town in the Sitamarhi district of the Indian state of Bihar.
  • B. Riga chosen
    Riga is the capital and largest city of Latvia, a historic cultural and economic hub on the Baltic Sea known for its Art Nouveau architecture and significant port.
  • C. Liepāja, Latvia
    Liepāja is a major port city on Latvia’s Baltic Sea coast, known for its historic architecture, naval heritage, and cultural life.
  • D. Riga Planning Region
    Riga Planning Region is an administrative planning area in Latvia that encompasses the capital city of Riga and its surrounding municipalities for regional development and coordination.
  • E. Valmiera
    Valmiera is a historic city in northern Latvia, situated on the Gauja River and known today as a regional economic and cultural center in the Vidzeme region.
  • 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_69ab4ac14040819098b13f4a27d5c8ff completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd48241c48190bc80418212e33bc8 completed March 7, 2026, 7:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98b250548190ad5226f2a2937a58 completed March 10, 2026, 4:06 a.m.
Created at: March 6, 2026, 9:49 p.m.