Triple

T13441981
Position Surface form Disambiguated ID Type / Status
Subject Jacek E320384 entity
Predicate hasVariant P455 FINISHED
Object Hyacinth E242957 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: Hyacinth | Statement: [Jacek, hasVariant, Hyacinth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hyacinth
Context triple: [Jacek, hasVariant, Hyacinth]
  • A. Hyacinth chosen
    Hyacinth is a given name of Greek origin, historically associated with mythological and floral imagery and used for people of any gender.
  • B. Ixia
    Ixia is a genus of flowering plants native to South Africa, known for their colorful, star-shaped blooms often grown as ornamental garden and cut flowers.
  • C. Lysianka
    Lysianka is an urban-type settlement in central Ukraine that serves as a local administrative and cultural center within Cherkasy Oblast.
  • D. Pansy
    Pansy is a small unincorporated community located in Crosby County in the U.S. state of Texas.
  • E. Primrose
    Primrose is a small rural town located in Dane County, Wisconsin, known for its agricultural landscape and quiet countryside character.
  • 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_69d80761e6cc8190a90c844589998ecc completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaee704ac8190b4c7f4e0d3a88494 completed April 12, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7399421908190a7750e37c89a73f6 completed May 3, 2026, 12:03 p.m.
Created at: April 9, 2026, 9:40 p.m.