Triple

T6689009
Position Surface form Disambiguated ID Type / Status
Subject Waddinxveen E152575 entity
Predicate borderedBy P224 FINISHED
Object Alphen aan den Rijn E167487 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: Alphen aan den Rijn | Statement: [Waddinxveen, borderedBy, Alphen aan den Rijn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alphen aan den Rijn
Context triple: [Waddinxveen, borderedBy, Alphen aan den Rijn]
  • A. Alphen aan den Rijn chosen
    Alphen aan den Rijn is a Dutch town and municipality situated along the Oude Rijn river in the western Netherlands.
  • 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. 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.
  • D. Zoeterwoude
    Zoeterwoude is a small Dutch municipality and village known for its rural character and location near Leiden in the province of South Holland.
  • E. Roosendaal
    Roosendaal is a city in the southern Netherlands known as a regional center for commerce and transport near the Belgian border.
  • 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_69c6880687b08190805278b504d1c92c completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6b14feb28819097bc157df8a2f96e completed March 27, 2026, 4:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69d178a6467c8190aab201fb12d2a64e completed April 4, 2026, 8:46 p.m.
Created at: March 27, 2026, 2:04 p.m.