Triple

T18318955
Position Surface form Disambiguated ID Type / Status
Subject Charlie Appleby E438819 entity
Predicate trained P3665 FINISHED
Object Masar 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: Masar | Statement: [Charlie Appleby, trained, Masar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Masar
Context triple: [Charlie Appleby, trained, Masar]
  • A. Masar chosen
    Masar is a British Thoroughbred racehorse best known for winning the 2018 Epsom Derby for Godolphin.
  • B. Masara
    Masara is an alternate name for the Masalit language, a Nilo-Saharan language spoken primarily by the Masalit people in western Sudan and eastern Chad.
  • C. Masarra
    Masarra is a passenger station on Cairo Metro’s Line 2 serving commuters in the Cairo metropolitan area.
  • D. Maasara
    Maasara is an industrial and residential district in the Greater Cairo area of Egypt, known for its factories and proximity to the Nile.
  • E. Masass
    Masass was a leader associated with the Northwest Indian Confederacy, a coalition of Native American tribes that resisted U.S. expansion in the late 18th and early 19th centuries.
  • 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_69d8b916a2d081909e249e4902f6aad9 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e50aa342a881909afcd995405027af completed April 19, 2026, 5:02 p.m.
Created at: April 10, 2026, 10:36 a.m.