Triple

T16238056
Position Surface form Disambiguated ID Type / Status
Subject Sidcup E394166 entity
Predicate postcodeArea P920 FINISHED
Object DA E237398 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: DA | Statement: [Sidcup, postcodeArea, DA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DA
Context triple: [Sidcup, postcodeArea, DA]
  • A. DA chosen
    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
    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 (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_69d87f2171208190951025e526947816 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2455c7a3c81909e3b42edf03be43e completed April 17, 2026, 2:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a000edaf76c8190acc01f58845e570a completed May 10, 2026, 4:51 a.m.
Created at: April 10, 2026, 5:04 a.m.