Triple

T12990963
Position Surface form Disambiguated ID Type / Status
Subject Mama Africa E321903 entity
Predicate hasPart P35 FINISHED
Object Dorcas E106597 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: Dorcas | Statement: [Mama Africa, hasPart, Dorcas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dorcas
Context triple: [Mama Africa, hasPart, Dorcas]
  • A. Dorcas chosen
    Dorcas is the young, enigmatic woman whose tragic love affair and death drive the central events and emotional tensions in Toni Morrison's novel "Jazz."
  • B. Dorcas
    Dorcas is a biblical woman from the New Testament, known for her charitable works and acts of kindness toward the poor.
  • C. Dorcas Good
    Dorcas Good was one of the youngest individuals accused of witchcraft during the Salem witch trials in 1692.
  • D. Dorcas Malvin
    Dorcas Malvin is a fictional character in Nathaniel Hawthorne’s short story “Roger Malvin’s Burial,” serving as the devoted daughter whose fate is tragically entwined with her father’s unburied death and her lover’s lingering guilt.
  • E. Lydia
    Lydia was an ancient Iron Age kingdom in western Anatolia, renowned for its wealth, early coinage, and powerful kings such as Croesus.
  • 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_69d8076479b8819090afce3591939cdf completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e7765788190a9503ef055bc30ca completed April 10, 2026, 10:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8fb70f481908a9a4ca04d6bf93b completed May 3, 2026, 2:54 a.m.
Created at: April 9, 2026, 8:43 p.m.