Triple

T20472372
Position Surface form Disambiguated ID Type / Status
Subject Elizabeth March E502223 entity
Predicate portrayedBy P1507 FINISHED
Object Claire Danes 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: Claire Danes | Statement: [Elizabeth March, portrayedBy, Claire Danes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Claire Danes
Context triple: [Elizabeth March, portrayedBy, Claire Danes]
  • A. Claire Danes chosen
    Claire Danes is an American actress acclaimed for her roles in projects such as the television series "Homeland" and the film "Romeo + Juliet."
  • B. Kim Raver
    Kim Raver is an American actress best known for her roles on television series such as "24," "Grey's Anatomy," and "Third Watch."
  • C. Jennifer Connelly
    Jennifer Connelly is an American actress acclaimed for her versatile performances in films ranging from independent dramas to major Hollywood productions, including her Oscar-winning role in "A Beautiful Mind."
  • D. Michelle Williams
    Michelle Williams is an American singer and actress best known as one of the lead vocalists of the Grammy-winning R&B group Destiny's Child.
  • E. Michelle Williams
    Michelle Williams is an acclaimed American actress known for her emotionally nuanced performances in both independent films and major studio productions, earning multiple Academy Award and Golden Globe nominations and wins.
  • 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_69e0b4ae5f1081908768b0c9a3a0bf38 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6996197908190b6570e2a7fd6cf67 completed April 20, 2026, 9:23 p.m.
Created at: April 16, 2026, 11:33 a.m.