Triple

T11056878
Position Surface form Disambiguated ID Type / Status
Subject Harriet Tubman E261398 entity
Predicate approximateNumberOfPeopleGuidedToFreedom P8803 FINISHED
Object dozens LITERAL 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: dozens | Statement: [Harriet Tubman, approximateNumberOfPeopleGuidedToFreedom, dozens]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfPeopleGuidedToFreedom
Context triple: [Harriet Tubman, approximateNumberOfPeopleGuidedToFreedom, dozens]
  • A. estimatedNumberOfPeopleSaved chosen
    Indicates the approximate count of individuals whose lives were preserved or harm was averted as a result of a particular action, intervention, or entity.
  • B. estimatedNumberOfSurvivorsAtLiberation
    Indicates the approximate count of individuals who were still alive at the time a camp or similar site was liberated.
  • C. estimatedNumberOfPeopleDeported
    Indicates the approximate count of individuals who were forcibly removed or expelled from a place or country.
  • D. numberOfJewsSaved
    Indicates the quantity of Jewish individuals who were rescued or preserved from harm, danger, or persecution in a given context.
  • E. approximateNumberOfRefugeesTransported
    Indicates an estimated count of refugees who were transported in the described event or context.
  • F. None of above.

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_69d6aa98650481908609c7c56bfa7902 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d798a2404c819090cb0825a67a64fa completed April 9, 2026, 12:16 p.m.
PD Predicate disambiguation batch_69d7440da46c8190a77380d5d747ac9c completed April 9, 2026, 6:15 a.m.
Created at: April 8, 2026, 9:26 p.m.