Triple

T11571671
Position Surface form Disambiguated ID Type / Status
Subject Sharon Kristin Harmon E274400 entity
Predicate hasMiddleName P143 FINISHED
Object Kristin E608731 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: Kristin | Statement: [Sharon Kristin Harmon, hasMiddleName, Kristin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kristin
Context triple: [Sharon Kristin Harmon, hasMiddleName, Kristin]
  • A. Kristin
    Kristin is one of the official mascots of the 1994 Winter Olympics held in Lillehammer, Norway.
  • B. Kristin
    Kristin is the central female protagonist of Sigrid Undset’s historical novel trilogy "Kristin Lavransdatter," set in medieval Norway.
  • C. Kristin chosen
    Kristin is a feminine given name commonly used in English-speaking and Scandinavian countries, often considered a variant of Christine or Christina.
  • D. Kristin
    Kristin is the given name of the acclaimed British-French actress Kristin Scott Thomas, known for her roles in films such as "The English Patient" and "Four Weddings and a Funeral."
  • E. Kristen
    Kristen is the central protagonist of the psychological horror film "The Ward," around whom the mysterious and unsettling events of the story revolve.
  • 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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88dd6913881908becf188c0a7a275 completed April 10, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69e6e8eface48190a2ed3275191b01ea completed April 21, 2026, 3:03 a.m.
Created at: April 8, 2026, 9:38 p.m.