Triple

T16293133
Position Surface form Disambiguated ID Type / Status
Subject Unna district E395574 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object UN E456755 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: UN | Statement: [Unna district, hasVehicleRegistrationCode, UN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UN
Context triple: [Unna district, hasVehicleRegistrationCode, UN]
  • A. UN
    The UN is an international organization founded in 1945 that brings together most of the world’s countries to promote peace, security, cooperation, and human rights.
  • B. UN chosen
    UN is the vehicle registration code for the German town of Unna in the state of North Rhine-Westphalia.
  • C. UNU
    UNU is the United Nations University, a global think tank and postgraduate teaching organization of the UN system focused on research and capacity-building for sustainable development and peace.
  • D. NU
    NU is a leading Japanese national research university located in Nagoya, known for its strong programs in science, engineering, and the humanities.
  • E. NU
    NU is the official two-letter Canada Post abbreviation for the northern Canadian territory of Nunavut.
  • 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_69d87f22c7248190a54c949738441e2e completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e25e2aee6881909fd28547f135427c completed April 17, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a001f97895081909f22ded3507afe14 completed May 10, 2026, 6:03 a.m.
Created at: April 10, 2026, 5:05 a.m.