Triple

T14420437
Position Surface form Disambiguated ID Type / Status
Subject Opuntian Locris E357567 entity
Predicate hasPort P35 FINISHED
Object Kynos E1098748 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: Kynos | Statement: [Opuntian Locris, hasPort, Kynos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kynos
Context triple: [Opuntian Locris, hasPort, Kynos]
  • A. Kynos chosen
    Kynos was an ancient Greek city of Opuntian Locris, known from classical sources as a coastal settlement in central Greece.
  • B. Karneios
    Karneios is an ancient Greek month, particularly in the Spartan calendar, associated with the festival of Karneia in honor of Apollo Karneios.
  • C. Deino
    Deino is one of the three Graeae in Greek mythology, ancient sea-daimones who shared a single eye and tooth among them and served as prophetic guardians.
  • D. Vulpius
    Vulpius is a German surname most notably associated with Christiane Vulpius, the longtime companion and later wife of writer Johann Wolfgang von Goethe.
  • E. Damastes
    Damastes is a figure from Greek mythology better known by the epithet Procrustes, a bandit infamous for violently stretching or cutting his victims to make them fit an iron bed.
  • 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_69d82793421c8190861eb0e673b085de completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de910eb354819089d5d5a46919eb49 completed April 14, 2026, 7:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd648784048190a9c7e95bfeec8b23 completed May 8, 2026, 4:20 a.m.
Created at: April 10, 2026, 1:18 a.m.