Triple

T16078720
Position Surface form Disambiguated ID Type / Status
Subject Samuel Lipman E390042 entity
Predicate citizenshipStatusDuringCase P31432 FINISHED
Object non-citizen resident of the United States 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: non-citizen resident of the United States | Statement: [Samuel Lipman, citizenshipStatusDuringCase, non-citizen resident of the United States]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: citizenshipStatusDuringCase
Context triple: [Samuel Lipman, citizenshipStatusDuringCase, non-citizen resident of the United States]
  • A. immigrationStatusBeforeCitizenship
    Indicates the legal immigration status an individual held prior to obtaining citizenship.
  • B. dualCitizenshipStatus
    Indicates that an entity holds legal citizenship in two different countries simultaneously.
  • C. citizenshipDuringLifetime chosen
    Indicates that an entity held citizenship in a particular country or political unit at some point during its lifetime.
  • D. citizenshipType
    Indicates the specific legal category or status of an individual's citizenship in relation to a state or country.
  • E. citizenshipStatusAfterMarriage
    Indicates the change or resulting state of a person's citizenship that occurs as a consequence of their marriage.
  • 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1ff63edb0819092cbb671967bbdcd completed April 17, 2026, 9:37 a.m.
PD Predicate disambiguation batch_69e1827ad7c88190b867da511cbfb7fa completed April 17, 2026, 12:44 a.m.
Created at: April 10, 2026, 4:57 a.m.