Triple

T13111902
Position Surface form Disambiguated ID Type / Status
Subject Battle of Artemisium E310992 entity
Predicate belligerent P375 FINISHED
Object Athens E12615 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: Athens | Statement: [Battle of Artemisium, belligerent, Athens]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Athens
Context triple: [Battle of Artemisium, belligerent, Athens]
  • A. Athens chosen
    Athens is Greece’s largest city and a historic center of ancient civilization, renowned as the birthplace of democracy and Western philosophy.
  • B. Athens
    Athens is a historic college town in northeastern Georgia, best known as the home of the University of Georgia and for its vibrant music and arts scene.
  • C. Athens
    Athens is a small city in northern Alabama known as the county seat of Limestone County and part of the Huntsville-Decatur metropolitan area.
  • D. Athens
    Athens is a small town in Mercer County, West Virginia, best known as the home of Concord University.
  • E. Athens
    Athens is a small rural municipality in eastern Ontario, Canada, known for its historic village character and proximity to the Thousand Islands region.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9817e4f408190b77c198b4157d77a completed April 10, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f716b1c7c081909154a59516b59d63 completed May 3, 2026, 9:34 a.m.
Created at: April 9, 2026, 9:05 p.m.