Triple

T23059802
Position Surface form Disambiguated ID Type / Status
Subject M. P. Shiel E574264 entity
Predicate placeOfBirth P1 FINISHED
Object Montserrat 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: Montserrat | Statement: [M. P. Shiel, placeOfBirth, Montserrat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montserrat
Context triple: [M. P. Shiel, placeOfBirth, Montserrat]
  • A. Montserrat chosen
    Montserrat is a small Caribbean island and British Overseas Territory known for its volcanic activity and lush, mountainous landscape.
  • B. Montserrat massif
    Montserrat massif is a distinctive multi-peaked mountain range in Catalonia, Spain, famed for its unique rock formations and the Montserrat Monastery.
  • C. Monte Grande
    Monte Grande is a suburban city in the Buenos Aires metropolitan area of Argentina, known as the administrative seat of the Esteban Echeverría Partido.
  • D. Monte
    Monte was the nickname of Monte Irvin, a Hall of Fame American baseball player renowned as one of the early Black stars to break Major League Baseball’s color barrier.
  • E. Monte
    Monte is a masculine given name, often used in English-speaking countries, that can be a standalone name or a diminutive of names like Montgomery.
  • 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_69e245ba7ae48190be606dbc54120e39 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1899f359081909e89e19db3833a3d completed April 29, 2026, 4:31 a.m.
Created at: April 17, 2026, 3:55 p.m.