Triple

T14778205
Position Surface form Disambiguated ID Type / Status
Subject Nadine Franklin E347318 entity
Predicate closeFriend P8712 FINISHED
Object Krista E375468 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: Krista | Statement: [Nadine Franklin, closeFriend, Krista]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Krista
Context triple: [Nadine Franklin, closeFriend, Krista]
  • A. Krista chosen
    Krista is a feminine given name, typically considered a variant of Christina and used in various European and English-speaking countries.
  • B. Kristi
    Kristi is a feminine given name commonly used in English-speaking countries, often as a variant of Kristy or Christina.
  • C. Kristen
    Kristen is a central female character in the romantic comedy film "Think Like a Man," whose love life and personal growth are explored through the movie’s ensemble relationship dynamics.
  • D. Kristen
    Kristen is a feminine given name commonly used in English-speaking countries, often associated with notable figures in entertainment and public life.
  • 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_69d822e9b9e08190bedcc31a163fda82 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec817c39081909b08a0ffdfce9936 completed April 14, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24b626c48190a6aa9eda43539246 completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:31 a.m.