Triple

T18600515
Position Surface form Disambiguated ID Type / Status
Subject Foster family E454607 entity
Predicate hasMember P10 FINISHED
Object Dr. Foster 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: Dr. Foster | Statement: [Foster family, hasMember, Dr. Foster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dr. Foster
Context triple: [Foster family, hasMember, Dr. Foster]
  • A. Dr. Foster chosen
    Dr. Foster is a fictional character in Toni Morrison’s novel "Song of Solomon," known primarily as the father of Ruth Foster Dead.
  • B. Dr. Mumford
    Dr. Mumford is the fictional psychologist protagonist of the 1999 comedy-drama film "Mumford," known for his unconventional therapeutic methods in a small town.
  • C. Dr. Harper
    Dr. Harper is a character in the horror film "The Boogeyman," serving as a key figure in the story’s unfolding supernatural terror.
  • D. Dr. Fagan
    Dr. Fagan is a comically unscrupulous and financially desperate headmaster of a disreputable Welsh boarding school in Evelyn Waugh’s satirical novel "Decline and Fall."
  • E. Dr. Woods
    Dr. Woods was a notable individual significant enough in his community or field to have a house named in his honor.
  • 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_69d8d38ae7e081908a98df1251842402 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5475018548190a2f497081af7ce55 completed April 19, 2026, 9:21 p.m.
Created at: April 10, 2026, 11:45 a.m.