Triple

T9972822
Position Surface form Disambiguated ID Type / Status
Subject The Women of Brewster Place E196249 entity
Predicate hasProtagonist P8706 FINISHED
Object Theresa E75291 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: Theresa | Statement: [The Women of Brewster Place, hasProtagonist, Theresa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Theresa
Context triple: [The Women of Brewster Place, hasProtagonist, Theresa]
  • A. Theresa chosen
    Theresa is a feminine given name of Greek origin, commonly associated in modern times with figures such as former UK Prime Minister Theresa May.
  • B. Teressa
    Teressa is a Nicobarese language variety spoken by the indigenous community on Teressa Island in India’s Nicobar archipelago.
  • C. Juliana
    Juliana is a feminine given name of Latin origin, commonly used in various European and Latin American countries.
  • D. Juliana
    Juliana is an Old English religious poem attributed to the Anglo-Saxon poet Cynewulf, recounting the legend and martyrdom of Saint Juliana.
  • E. Juliana
    Juliana was Queen of the Netherlands from 1948 to 1980, known for her down-to-earth style and role in guiding the country through postwar reconstruction and decolonization.
  • 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_69ca82eea2b88190a0e511d21a31f386 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb7bb03688190a3f4fc1988b8fafa completed April 2, 2026, 12:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d23dd3e47c819095fef68b9939ec19 completed April 5, 2026, 10:47 a.m.
Created at: March 30, 2026, 8:48 p.m.