Triple

T12723006
Position Surface form Disambiguated ID Type / Status
Subject Daphne Mitsotaki E304031 entity
Predicate givenName P17 FINISHED
Object Daphne E88548 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: Daphne | Statement: [Daphne Mitsotaki, givenName, Daphne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daphne
Context triple: [Daphne Mitsotaki, givenName, Daphne]
  • A. Daphne chosen
    Daphne is a nymph from Greek mythology best known for being pursued by Apollo and transformed into a laurel tree to escape him.
  • B. Daphne
    Daphne is a coastal city in Baldwin County, Alabama, situated along the eastern shore of Mobile Bay.
  • C. Daphne
    Daphne is an HTTP, HTTP/2, and WebSocket server for ASGI applications, commonly used to serve Django and other Python async web frameworks.
  • D. Daphne
    "Daphne" is a fast, swinging jazz composition by guitarist Django Reinhardt that has become a recognized standard in the gypsy jazz repertoire.
  • E. Leontine
    Leontine is a feminine given name, used as a variant of names like Leona and Leontina, with roots in Latin meaning "lion-like" or "lioness."
  • 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_69d7bdf084148190ab9d513dc0735af4 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d964148f988190a4d0e7b41614fa64 completed April 10, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c841edc81909147d30c51471c47 completed May 2, 2026, 10:36 p.m.
Created at: April 9, 2026, 5:24 p.m.