Triple

T2869787
Position Surface form Disambiguated ID Type / Status
Subject Leslie Spier E63530 entity
Predicate name P16 FINISHED
Object Leslie Spier E63530 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: Leslie Spier | Statement: [Leslie Spier, name, Leslie Spier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leslie Spier
Context triple: [Leslie Spier, name, Leslie Spier]
  • A. Leslie Spier chosen
    Leslie Spier was an American anthropologist known for his influential work in cultural anthropology and ethnography, particularly among Native American groups in the American Southwest and Northwest.
  • B. Katherine Spiegel
    Katherine Spiegel was the wife of prominent American film director and producer Mervyn LeRoy.
  • C. Leslie Easterbrook
    Leslie Easterbrook is an American actress best known for her role as Sergeant Debbie Callahan in the "Police Academy" film series.
  • D. Leslie Vadasz
    Leslie Vadasz is a Hungarian-American engineer and technology executive best known as one of Intel’s founding members and a key contributor to the development of the microprocessor and semiconductor memory.
  • E. Sally Menke
    Sally Menke was an American film editor best known for her long-time collaboration with director Quentin Tarantino on films such as Pulp Fiction, Kill Bill, and Inglourious Basterds.
  • 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_69ab4c42fb8c8190b36e161d47c03b81 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdfe15ff081908dd1dad62c292b2b completed March 7, 2026, 8:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69b2249f50008190921040166f6036b9 completed March 12, 2026, 2:27 a.m.
Created at: March 6, 2026, 10:02 p.m.