Triple

T578226
Position Surface form Disambiguated ID Type / Status
Subject Rum E15002 entity
Predicate locatedNear P294 FINISHED
Object Muck E16789 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: Muck | Statement: [Rum, locatedNear, Muck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Muck
Context triple: [Rum, locatedNear, Muck]
  • A. Muck chosen
    Muck is one of the Small Isles of Scotland, a tiny Inner Hebridean island known for its rugged coastline, wildlife, and remote rural character.
  • B. Moss
    Moss is a coastal town and municipality in southeastern Norway known for its industrial history, cultural life, and role as a regional hub in Østfold.
  • C. Moss
    Moss is a masculine given name most notably borne by American playwright and director Moss Hart.
  • D. Gliz
    Gliz is one of the official mascots of the 2006 Winter Olympics in Turin, Italy, depicted as a stylized anthropomorphic ice cube symbolizing winter sports and modernity.
  • E. The Stump
    The Stump is the popular nickname for the towering parish church of St Botolph in Boston, Lincolnshire, renowned for its massive, landmark tower visible for miles across the flat surrounding landscape.
  • 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_69a4935783b8819082b77726ec10cc42 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49b69fed88190b5558d4ebd5047a1 completed March 1, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69a501c1b8448190847197d984f211c3 completed March 2, 2026, 3:19 a.m.
Created at: March 1, 2026, 7:33 p.m.