Triple

T14749681
Position Surface form Disambiguated ID Type / Status
Subject Life of Dion E346569 entity
Predicate setting P1957 FINISHED
Object Syracuse E148060 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: Syracuse | Statement: [Life of Dion, setting, Syracuse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Syracuse
Context triple: [Life of Dion, setting, Syracuse]
  • A. Syracuse
    Syracuse is a mid-sized city in central New York State known for Syracuse University, its role as a regional economic and cultural hub, and its snowy winters.
  • B. Syracuse chosen
    Syracuse is an ancient and historically significant city on the eastern coast of Sicily, renowned as a powerful Greek colony and cultural center in antiquity.
  • C. Syracuse
    Syracuse is a suburban city in Davis County, northern Utah, known for its rapid growth and proximity to the Great Salt Lake and Antelope Island.
  • D. Utica
    Utica was an ancient Phoenician colony in North Africa that became one of the earliest and most important urban centers in the western Mediterranean.
  • E. Utica
    Utica is a small town in Hinds County, Mississippi, known for its rural character and historic Southern setting.
  • 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_69d822e6f1c88190bc494d491a907114 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7d2e1748190b16ede681fe52872 completed April 14, 2026, 11:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb89ea388190b356df74e36023f7 completed May 8, 2026, 3:04 p.m.
Created at: April 10, 2026, 1:30 a.m.