Triple

T17102561
Position Surface form Disambiguated ID Type / Status
Subject Lünen E415014 entity
Predicate vehicleRegistrationCode 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: [Lünen, vehicleRegistrationCode, UN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UN
Context triple: [Lünen, vehicleRegistrationCode, 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_69d886cfc8e88190b05ba466edd35591 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dc2495c88190b5b16a006a994faf completed April 18, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0139fdda488190a1ca5c7ca875e044 completed May 11, 2026, 2:07 a.m.
Created at: April 10, 2026, 5:35 a.m.