Triple

T14361974
Position Surface form Disambiguated ID Type / Status
Subject Aqua Anio Vetus E356126 entity
Predicate followedBy P78 FINISHED
Object Aqua Marcia E358751 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: Aqua Marcia | Statement: [Aqua Anio Vetus, followedBy, Aqua Marcia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aqua Marcia
Context triple: [Aqua Anio Vetus, followedBy, Aqua Marcia]
  • A. Aqua Marcia chosen
    Aqua Marcia was one of ancient Rome’s longest and most celebrated aqueducts, renowned for supplying the city with abundant, high-quality water.
  • B. Aqua
    Aqua is the distinctive, glossy, and translucent graphical user interface introduced by Apple for macOS, known for its vibrant colors, smooth animations, and skeuomorphic design elements.
  • C. Aqua
    Aqua is a popular bottled drinking water brand owned by the multinational food and beverage company Danone, widely sold in various markets, especially in Asia.
  • D. Aqua
    Aqua is a Danish-Norwegian pop group best known for their late-1990s Eurodance hits like "Barbie Girl."
  • E. Aqua Anio Vetus
    Aqua Anio Vetus was one of ancient Rome’s earliest major aqueducts, channeling water from the Aniene River to supply the growing city.
  • 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_69d82790a7e08190877e2d349b2e8d8e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8fabec088190bd8128371b29e958 completed April 14, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c4aba788190bd5ab8cbc772dcf1 completed May 8, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:15 a.m.