Triple

T20863173
Position Surface form Disambiguated ID Type / Status
Subject Erzhausen E513676 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object DA NE NERFINISHED

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: DA | Statement: [Erzhausen, vehicleRegistrationCode, DA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DA
Context triple: [Erzhausen, vehicleRegistrationCode, DA]
  • A. DA
    DA is a postcode area in southeast England covering parts of south-east London and northwest Kent, including towns such as Dartford and Sidcup.
  • B. DA chosen
    DA is the vehicle registration code for the German city of Darmstadt and its surrounding district in the state of Hesse.
  • C. DA
    DA is the official abbreviation for the United States Department of the Army, the federal agency responsible for organizing, training, and equipping the U.S. Army.
  • D. DA
    DA is the commonly used abbreviation for the Defence Academy of the United Kingdom, the institution responsible for advanced education and training of the UK’s armed forces and defence personnel.
  • E. DA
    DA is the Philippine government agency responsible for promoting agricultural development, ensuring food security, and supporting farmers and fisherfolk nationwide.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4f5b01081909452f654d2fc3f50 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c45d2ec4819098abbb901b9fcd87 completed April 21, 2026, 12:27 a.m.
Created at: April 16, 2026, 12:44 p.m.