Triple

T3221349
Position Surface form Disambiguated ID Type / Status
Subject Village of Greenwood Lake, New York E67517 entity
Predicate hasPublicSafety P464 FINISHED
Object local police department 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: local police department | Statement: [Village of Greenwood Lake, New York, hasPublicSafety, local police department]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasPublicSafety
Context triple: [Village of Greenwood Lake, New York, hasPublicSafety, local police department]
  • A. publicSafetyAgencyType
    Indicates the specific category or kind of public safety agency associated with an entity (e.g., police, fire, emergency medical services).
  • B. safetyRelevant
    Indicates that the associated entity, condition, or information has a direct impact on safety or is critical for preventing harm or accidents.
  • C. hasEmergencyServices chosen
    Indicates that the subject provides or is equipped with emergency response services (such as police, fire, or medical assistance).
  • D. notableSafety
    Indicates that an entity is recognized for having significant safety characteristics, performance, or impact relative to others.
  • E. hasSafetyInfrastructure
    Indicates that appropriate safety-related structures, systems, or measures are present for the referenced entity or environment.
  • 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_69ad858b8adc8190ad989712c87a476b completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adae1845408190b3eccd791231c69c completed March 8, 2026, 5:12 p.m.
PD Predicate disambiguation batch_69ad9e0bb6c48190a0659c67d40ee37c completed March 8, 2026, 4:04 p.m.
Created at: March 8, 2026, 3:08 p.m.