Triple

T9074850
Position Surface form Disambiguated ID Type / Status
Subject Woluwe-Saint-Pierre E217458 entity
Predicate borderedBy P224 FINISHED
Object Kraainem E611290 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: Kraainem | Statement: [Woluwe-Saint-Pierre, borderedBy, Kraainem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kraainem
Context triple: [Woluwe-Saint-Pierre, borderedBy, Kraainem]
  • A. Kraainem chosen
    Kraainem is a Dutch- and French-speaking suburban municipality on the eastern edge of Brussels in the Flemish Brabant province of Belgium.
  • B. Kuressaare
    Kuressaare is the main town on Estonia’s Saaremaa island, known for its well-preserved medieval castle and seaside spa resort atmosphere.
  • C. Kõrgessaare
    Kõrgessaare is a small settlement on the island of Hiiumaa in western Estonia, known for its coastal location and rural character.
  • D. Viedma
    Viedma is a city in northern Patagonia and one of the oldest settlements in Argentina, serving as the capital of Río Negro Province.
  • E. Ruhnu
    Ruhnu is a small Estonian island in the Gulf of Riga, known for its remote location, traditional wooden lighthouse and church, and unique cultural heritage.
  • 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_69ca83d6c14c8190bc056d927f00a2a2 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc95c4026c8190b553aedb9f4beabb completed April 1, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69cffdfe16c4819092c884bc3fe5daeb completed April 3, 2026, 5:50 p.m.
Created at: March 30, 2026, 7:12 p.m.