Triple

T5670084
Position Surface form Disambiguated ID Type / Status
Subject Pieter Zeeman E124951 entity
Predicate residence P75 FINISHED
Object Amsterdam E989 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: Amsterdam | Statement: [Pieter Zeeman, residence, Amsterdam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amsterdam
Context triple: [Pieter Zeeman, residence, Amsterdam]
  • A. Amsterdam chosen
    Amsterdam is the largest city in the Netherlands, renowned as a historic commercial and cultural center characterized by its canals, trading heritage, and role as the country’s principal metropolis.
  • B. Rotterdam
    Rotterdam is a major Dutch port city known for having one of the world’s largest harbors and striking modern architecture.
  • C. Haarlem
    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.
  • D. The Hague
    The Hague is a major Dutch city known as the seat of the Netherlands’ government and home to numerous international courts and organizations, including the International Court of Justice.
  • E. Leeuwarden
    Leeuwarden is a historic city in the northern Netherlands, known as the capital of the province of Friesland and for its rich cultural and architectural heritage.
  • 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_69c00828906881908966f270b8f130cf completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02349b570819090f754a2f25e4cf3 completed March 22, 2026, 5:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c059ce87448190ac88e79ed4c0f47b completed March 22, 2026, 9:06 p.m.
Created at: March 22, 2026, 3:43 p.m.