Triple

T25597239
Position Surface form Disambiguated ID Type / Status
Subject Improving Access to Services for Persons with Limited English Proficiency E641687 entity
Predicate objective P79 FINISHED
Object standardize language access obligations across agencies LITERAL FINISHED

How this triple was built (1 step)

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: standardize language access obligations across agencies | Statement: [Improving Access to Services for Persons with Limited English Proficiency, objective, standardize language access obligations across agencies]

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_69e75dc60d108190b7e2419e36b0134b completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f9a420f08190a8ed8c9a8c245fc4 completed May 2, 2026, 1:18 p.m.
Created at: April 21, 2026, 4:28 p.m.