Triple

T9259455
Position Surface form Disambiguated ID Type / Status
Subject Lier E222534 entity
Predicate hasTwinTown P919 FINISHED
Object Haarlem E80096 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: Haarlem | Statement: [Lier, hasTwinTown, Haarlem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haarlem
Context triple: [Lier, hasTwinTown, Haarlem]
  • A. Haarlem chosen
    Haarlem is a historic Dutch city in the province of North Holland, known for its medieval architecture, cultural heritage, and role as a regional center near Amsterdam.
  • B. Utrecht
    Utrecht is a historic city and province in the central Netherlands, known for its medieval old town, canals, and role as a religious and cultural center.
  • C. Nijmegen
    Nijmegen is a historic Dutch city near the German border that played a crucial strategic role during World War II, particularly in the Allied advance in 1944.
  • D. Rijswijk
    Rijswijk is a town in the western Netherlands, near The Hague, historically notable as the site where the 1697 Treaty of Rijswijk ended the Nine Years' War.
  • E. Hilversum
    Hilversum is a Dutch city known as the country’s main media and broadcasting center, located in the province of North Holland.
  • 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_69ca841e4cd481908e738c74e958eaea completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd0714317481908405f857a4f49e74 completed April 1, 2026, 11:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69d87dfc46e08190bea27c11b987cb6d completed April 10, 2026, 4:35 a.m.
Created at: March 30, 2026, 7:32 p.m.