Triple

T17148730
Position Surface form Disambiguated ID Type / Status
Subject New Jersey Department of Human Services E416163 entity
Predicate alsoServesLanguage P18404 FINISHED
Object Spanish 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: Spanish | Statement: [New Jersey Department of Human Services, alsoServesLanguage, Spanish]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: alsoServesLanguage
Context triple: [New Jersey Department of Human Services, alsoServesLanguage, Spanish]
  • A. hasLanguages
    Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
  • B. usesWorkingLanguagesOf
    Indicates that one entity employs or operates using the working languages associated with another entity.
  • C. isLanguageOf
    Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
  • D. isWorkingLanguageOf chosen
    Indicates that a particular language is officially used as a medium of work, communication, or operation within a specified organization, institution, or context.
  • E. usesLanguageFor
    Indicates that an entity employs a particular language as a tool or medium to perform some activity, function, or purpose.
  • 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_69d886d279c081909f8ff1f743ddeb69 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f4059d90819092d3609326fa3130 completed April 18, 2026, 9:13 p.m.
PD Predicate disambiguation batch_69e3830d2a90819092386717dc56f0e8 completed April 18, 2026, 1:11 p.m.
Created at: April 10, 2026, 5:36 a.m.