Triple

T11940087
Position Surface form Disambiguated ID Type / Status
Subject Superfund program E284150 entity
Predicate hasHealthGoal P102263 FINISHED
Object prevent exposure to toxic contaminants 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: prevent exposure to toxic contaminants | Statement: [Superfund program, hasHealthGoal, prevent exposure to toxic contaminants]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasHealthGoal
Context triple: [Superfund program, hasHealthGoal, prevent exposure to toxic contaminants]
  • A. hasMaintenanceGoal
    Indicates that an entity is associated with a specific objective or target related to its upkeep, repair, or ongoing maintenance activities.
  • B. hasTherapeuticGoal
    Indicates that an action, treatment, or intervention is undertaken with the intention of achieving a specific therapeutic or health-related outcome.
  • C. hasPlanningGoal
    Indicates that an entity is associated with, or directed toward achieving, a specific planning objective or target state.
  • D. hasPrimaryGoal
    Indicates that an entity’s main or most important objective is the specified goal.
  • E. hasManagementGoal
    Indicates that an entity is associated with a specific management objective or target it is intended to achieve or support.
  • F. None of above. chosen

Provenance (4 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_69d6ab2ce9c48190b5d39511b524f666 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903415d2481909d84e6727454b9fe completed April 10, 2026, 2:03 p.m.
PD Predicate disambiguation batch_69d8bb3af0188190bfb22be5c97b3349 completed April 10, 2026, 8:56 a.m.
PDg Predicate description generation batch_69d8d399d58c81908dab572aa82426d7 completed April 10, 2026, 10:40 a.m.
Created at: April 8, 2026, 9:45 p.m.