Triple

T22310868
Position Surface form Disambiguated ID Type / Status
Subject Rachel Stevenson E551507 entity
Predicate hasGivenName P17 FINISHED
Object Rachel 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: Rachel | Statement: [Rachel Stevenson, hasGivenName, Rachel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rachel
Context triple: [Rachel Stevenson, hasGivenName, Rachel]
  • A. Rachel chosen
    Rachel is a feminine given name of Hebrew origin meaning "ewe," historically associated with the biblical matriarch and widely used in many cultures.
  • B. Rachel
    Rachel is a fictional character portrayed by French actress Clémence Poésy, known for her roles in film and television dramas.
  • C. Rachel
    Rachel is a central protagonist in the Australian television drama series "The Newsreader," which follows the turbulent personal and professional lives of 1980s broadcast journalists.
  • D. Rachel
    Rachel is a central character in the contemporary romance novel "Kissing Lessons," involved in a story of teenage relationships, self-discovery, and emotional growth.
  • E. Rachel
    Rachel is a central protagonist in Emily Giffin's novel "Something Borrowed," whose romantic entanglements with her best friend's fiancé drive the story's themes of friendship, loyalty, and self-discovery.
  • 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_69e11e46c0188190800181a4233f28fe completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1574e7fc0819080e3e85001ab2c90 completed April 29, 2026, 12:56 a.m.
Created at: April 16, 2026, 8:42 p.m.