Triple

T1311953
Position Surface form Disambiguated ID Type / Status
Subject Białystok E28010 entity
Predicate twinCity P1072 FINISHED
Object Eindhoven E13694 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: Eindhoven | Statement: [Białystok, twinCity, Eindhoven]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eindhoven
Context triple: [Białystok, twinCity, Eindhoven]
  • A. Eindhoven chosen
    Eindhoven is a major city in the southern Netherlands known for its industrial and technological significance, particularly as a hub for electronics and design.
  • B. Tilburg
    Tilburg is a city in the southern Netherlands known historically as an industrial and textile center and now as a regional cultural and educational hub.
  • 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. 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.
  • E. Alphen aan den Rijn
    Alphen aan den Rijn is a Dutch town and municipality situated along the Oude Rijn river in the western Netherlands.
  • 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_69a498532c3481909223b74af2e578df completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c1572b1c8190ab978198c2d655c8 completed March 1, 2026, 10:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e337908819091bf126b5acad9df completed March 13, 2026, 3:02 a.m.
Created at: March 1, 2026, 7:55 p.m.