Triple

T2827831
Position Surface form Disambiguated ID Type / Status
Subject Misenum E54965 entity
Predicate near P350 FINISHED
Object Cumae E52280 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: Cumae | Statement: [Misenum, near, Cumae]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cumae
Context triple: [Misenum, near, Cumae]
  • A. Cumae chosen
    Cumae was an ancient Greek colony in Italy, renowned as one of the earliest Hellenic settlements in the West and famous for its oracle, the Cumaean Sibyl.
  • B. Kaiapoi
    Kaiapoi is a town in the Waimakariri District of Canterbury, New Zealand, known historically as a river port and service center for the surrounding rural area.
  • C. Hirapa
    Hirapa is a popular amusement park in Hirakata, Osaka, Japan, known for its variety of rides, seasonal events, and family-friendly attractions.
  • D. Kamiros
    Kamiros is an ancient city and archaeological site on the northwest coast of Rhodes, known for its well-preserved Hellenistic ruins and grid-planned layout.
  • E. Mauregard
    Mauregard is a small commune in the Seine-et-Marne department of the Île-de-France region in north-central France, situated near Paris Charles de Gaulle Airport.
  • 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_69ab49e100c0819082a40cb797383243 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde95d8148190bcae8b0659a5c116 completed March 7, 2026, 8:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69afceb20c508190ba87e102ba250a00 completed March 10, 2026, 7:56 a.m.
Created at: March 6, 2026, 9:59 p.m.