Triple

T8910903
Position Surface form Disambiguated ID Type / Status
Subject Strand E212177 entity
Predicate hasLandmark P105 FINISHED
Object Royal Courts of Justice E103317 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: Royal Courts of Justice | Statement: [Strand, hasLandmark, Royal Courts of Justice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Royal Courts of Justice
Context triple: [Strand, hasLandmark, Royal Courts of Justice]
  • A. Royal Courts of Justice chosen
    The Royal Courts of Justice is a major court building in London that houses the High Court and Court of Appeal of England and Wales.
  • B. Court of the Bank of England
    The Court of the Bank of England is the institution’s governing board, responsible for overseeing its strategy, operations, and key senior appointments.
  • C. Queen Mary Court
    Queen Mary Court is one of the principal historic Baroque buildings within the Old Royal Naval College complex in Greenwich, London.
  • D. Old Court
    Old Court is a historic quadrangle at Selwyn College, Cambridge, known for its traditional collegiate architecture and central role in college life.
  • E. Old Court
    Old Court is the historic central courtyard of Queens’ College, Cambridge, known for its traditional collegiate architecture and riverside setting.
  • 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_69ca8393b1808190bd4336787ffa2c40 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6523b9348190a7cefac9e73e2004 completed April 1, 2026, 12:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfba36f8cc8190ab57ddc99b7219d1 completed April 3, 2026, 1:01 p.m.
Created at: March 30, 2026, 6:55 p.m.