Triple

T20827100
Position Surface form Disambiguated ID Type / Status
Subject M2 Bradley E512730 entity
Predicate operator P179 FINISHED
Object Lebanon 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: Lebanon | Statement: [M2 Bradley, operator, Lebanon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lebanon
Context triple: [M2 Bradley, operator, Lebanon]
  • A. Lebanon chosen
    Lebanon is a small city in central Indiana, United States, serving as the county seat of Boone County and part of the greater Indianapolis metropolitan region.
  • B. Lebanon
    Lebanon is a small city in central Tennessee known as the home of Cumberland University and the headquarters of the Cracker Barrel restaurant chain.
  • C. Lebanon
    Lebanon is a small Middle Eastern country on the eastern shore of the Mediterranean Sea, known for its rich history, diverse religious and cultural heritage, and historic capital, Beirut.
  • D. The Lebanon
    "The Lebanon" is a politically charged 1984 synth-pop song by British band The Human League that comments on the Lebanese Civil War.
  • E. Lubāna
    Lubāna is a small town in eastern Latvia known for its proximity to the Lubāns Lake and surrounding wetlands.
  • 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_69e0b4ce39108190a6e8e5df4f1c8dc5 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c2fe54608190a061274bf4316610 completed April 21, 2026, 12:21 a.m.
Created at: April 16, 2026, 12:42 p.m.