Triple

T15768587
Position Surface form Disambiguated ID Type / Status
Subject Eindhoven railway and bus networks E382289 entity
Predicate connectsTo P845 FINISHED
Object Tilburg NE NERFINISHED

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: Tilburg | Statement: [Eindhoven railway and bus networks, connectsTo, Tilburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tilburg
Context triple: [Eindhoven railway and bus networks, connectsTo, Tilburg]
  • A. Tilburg chosen
    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.
  • B. Eindhoven
    Eindhoven is a major city in the southern Netherlands known for its industrial and technological significance, particularly as a hub for electronics and design.
  • C. 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.
  • D. Utrecht
    Utrecht is a small town in South Africa’s KwaZulu-Natal province, known for its scenic surroundings and historical significance dating back to the 19th century.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d86da09a10819082fe9797b23e4664 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e051951bac8190a7d45f3612c6de72 completed April 16, 2026, 3:03 a.m.
Created at: April 10, 2026, 4:47 a.m.