Triple

T14776865
Position Surface form Disambiguated ID Type / Status
Subject Royal Marines Reserve E347282 entity
Predicate hasGarrison P3479 FINISHED
Object RMR City of London E1119197 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: RMR City of London | Statement: [Royal Marines Reserve, hasGarrison, RMR City of London]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RMR City of London
Context triple: [Royal Marines Reserve, hasGarrison, RMR City of London]
  • A. RMR London chosen
    RMR London is a Royal Marines Reserve unit based in London that trains and supports part-time Royal Marines alongside their regular counterparts.
  • B. City of London
    The City of London is the historic and financial core of Greater London, renowned as one of the world’s leading global finance and business centers.
  • C. Metropolis (London)
    Metropolis (London) is the historic core area of Greater London that served as the primary urban and administrative center of the city during the 19th century.
  • D. Pool of London
    The Pool of London is a historic stretch of the River Thames in central London that long served as a key anchorage and trading hub for the city’s port.
  • E. Londiani
    Londiani is a town in Kenya’s Rift Valley region, known as a local commercial and transport hub within Kericho County.
  • 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_69d822e9b9e08190bedcc31a163fda82 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec817c39081909b08a0ffdfce9936 completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24b626c48190a6aa9eda43539246 completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:31 a.m.