Triple

T19371766
Position Surface form Disambiguated ID Type / Status
Subject Lydia Sigourney E484555 entity
Predicate givenName P17 FINISHED
Object Lydia NE NERFINISHED

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: Lydia | Statement: [Lydia Sigourney, givenName, Lydia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lydia
Context triple: [Lydia Sigourney, givenName, Lydia]
  • A. Lydia
    Lydia is a woman mentioned in the New Testament book of Acts, known as a dealer in purple cloth from Thyatira and one of the first recorded converts to Christianity in Europe.
  • B. Lydia
    Lydia was an ancient Iron Age kingdom in western Anatolia, renowned for its wealth, early coinage, and powerful kings such as Croesus.
  • C. Lydia
    Lydia is the youngest and most impulsive of the Bennet sisters in Jane Austen's novel "Pride and Prejudice."
  • D. Lydia chosen
    Lydia is a feminine given name of Greek origin, historically associated with the ancient region of Lydia and often interpreted to mean "woman from Lydia" or "beautiful one."
  • E. Lydia
    Lydia is a supporting character in the romantic drama film "Sliding Doors," which explores alternate realities in the life of the protagonist.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d305088190ad13571532aa454c completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e619b1b5fc819089f9fc43f407bbb0 completed April 20, 2026, 12:18 p.m.
Created at: April 10, 2026, 1:35 p.m.