Triple

T19366759
Position Surface form Disambiguated ID Type / Status
Subject Lezayre E484421 entity
Predicate borders P224 FINISHED
Object Maughold 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: Maughold | Statement: [Lezayre, borders, Maughold]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maughold
Context triple: [Lezayre, borders, Maughold]
  • A. Maughold chosen
    Maughold is a coastal parish and village on the Isle of Man known for its rugged cliffs, scenic coastline, and historic church with ancient Celtic crosses.
  • B. The Fortress
    The Fortress is a popular nickname for MAPFRE Stadium, the historic soccer-specific home of the Columbus Crew in Major League Soccer.
  • C. The Fortress
    The Fortress is a South Korean historical drama film depicting the Joseon court’s struggle for survival during the Qing invasion, directed by Hwang Dong-hyuk.
  • D. Reduta
    Reduta is a historic theatre building known as a cultural landmark and performance venue.
  • E. Unternehmen Zitadelle
    Unternehmen Zitadelle was the German codename for the major 1943 offensive on the Eastern Front that led to the Battle of Kursk, one of the largest tank battles in history.
  • 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_69d8e8d305088190ad13571532aa454c completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e619ac26d4819095836d737b629cf1 completed April 20, 2026, 12:18 p.m.
Created at: April 10, 2026, 1:35 p.m.