Triple

T8412078
Position Surface form Disambiguated ID Type / Status
Subject Deer Park station E198647 entity
Predicate hasStationCode P1289 FINISHED
Object DPK
DPK is the station code for Deer Park railway station, a commuter rail stop on Long Island, New York.
 E731562 NE FINISHED

How this triple was built (4 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: DPK | Statement: [Deer Park station, hasStationCode, DPK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DPK
Context triple: [Deer Park station, hasStationCode, DPK]
  • A. DPPA
    DPPA is the United Nations department responsible for conflict prevention, peacemaking, and supporting political and peacebuilding efforts worldwide.
  • B. DPG
    DPG is the commonly used abbreviation for the German Physical Society, one of the world’s largest and oldest organizations dedicated to advancing physics research and education.
  • C. DPH
    DPH is the Georgia state agency responsible for protecting and improving public health through disease prevention, health promotion, and emergency preparedness programs.
  • D. DPB
    DPB is the abbreviation for the APS Division of Physics of Beams, a unit of the American Physical Society focused on research and advancement in beam physics.
  • E. DPR
    DPR is the government agency responsible for managing and operating public parks, recreational facilities, and community programs in Washington, D.C.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: DPK
Triple: [Deer Park station, hasStationCode, DPK]
Generated description
DPK is the station code for Deer Park railway station, a commuter rail stop on Long Island, New York.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DPK
Target entity description: DPK is the station code for Deer Park railway station, a commuter rail stop on Long Island, New York.
  • A. DPPA
    DPPA is the United Nations department responsible for conflict prevention, peacemaking, and supporting political and peacebuilding efforts worldwide.
  • B. DPG
    DPG is the commonly used abbreviation for the German Physical Society, one of the world’s largest and oldest organizations dedicated to advancing physics research and education.
  • C. DPH
    DPH is the Georgia state agency responsible for protecting and improving public health through disease prevention, health promotion, and emergency preparedness programs.
  • D. DPB
    DPB is the abbreviation for the APS Division of Physics of Beams, a unit of the American Physical Society focused on research and advancement in beam physics.
  • E. DPR
    DPR is the government agency responsible for managing and operating public parks, recreational facilities, and community programs in Washington, D.C.
  • F. None of above. chosen

Provenance (5 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_69ca831201b481909e137936ef99ff11 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb83e0341c819080506e696131671e completed March 31, 2026, 8:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce0322d1448190aceaf7486c110ff7 completed April 2, 2026, 5:48 a.m.
NEDg Description generation batch_69ce07808098819087e896b87320aefd completed April 2, 2026, 6:06 a.m.
NED2 Entity disambiguation (via description) batch_69ce08759e1c81909c96caf3b571e1ca completed April 2, 2026, 6:11 a.m.
Created at: March 30, 2026, 6:05 p.m.