Triple

T4577103
Position Surface form Disambiguated ID Type / Status
Subject Singel E123164 entity
Predicate hasNotableBuilding P1544 FINISHED
Object Munttoren E24383 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: Munttoren | Statement: [Singel, hasNotableBuilding, Munttoren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Munttoren
Context triple: [Singel, hasNotableBuilding, Munttoren]
  • A. Munttoren chosen
    Munttoren is a historic clock and bell tower in central Amsterdam, originally part of the city’s medieval fortifications and now a notable canal-side landmark.
  • B. Schmalzturm
    Schmalzturm is a historic medieval tower in the Bavarian town of Landsberg am Lech, notable as a landmark of its old town fortifications.
  • C. Schmalzturm
    Schmalzturm is a historic medieval tower and notable architectural landmark in the Bavarian town of Weißenburg in Bayern, Germany.
  • D. Storvreten
    Storvreten is a residential locality within Botkyrka Municipality in the Stockholm County area of Sweden.
  • E. Murgtal
    Murgtal is a scenic valley in the northern Black Forest of Germany, known for its steep forested slopes, the River Murg, and traditional spa and timber towns.
  • 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_69bd46466c7081909d07f36be2d08804 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd58e153908190ac8f578e03aecdfc completed March 20, 2026, 2:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdd3ee510481909d481b157bd0b2bd completed March 20, 2026, 11:10 p.m.
Created at: March 20, 2026, 1:10 p.m.