Triple

T9938723
Position Surface form Disambiguated ID Type / Status
Subject Plandome station E194022 entity
Predicate code P1537 FINISHED
Object PDM
PDM is the station code for Plandome station on the Long Island Rail Road in New York.
 E830961 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: PDM | Statement: [Plandome station, code, PDM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: PDM
Context triple: [Plandome station, code, PDM]
  • A. PDM
    PDM is a modern Python package and dependency manager that emphasizes PEP 582 support and a streamlined, pyproject.toml-based workflow.
  • B. PTC
    PTC is an advanced safety system used on railroads to automatically prevent train collisions, overspeed derailments, and other dangerous movements.
  • C. PTC
    PTC is a Permanent Technical Committee, typically a standing expert group responsible for developing and maintaining technical standards or guidelines within a specific domain.
  • D. DPM
    DPM is the abbreviation for the División de Policía Militar, a military police division responsible for law enforcement and security duties within a nation's armed forces.
  • E. PMM
    PMM is the commonly used acronym for Perpignan Méditerranée Métropole, an intercommunal urban community centered on the city of Perpignan in southern France.
  • 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: PDM
Triple: [Plandome station, code, PDM]
Generated description
PDM is the station code for Plandome station on the Long Island Rail Road in New York.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: PDM
Target entity description: PDM is the station code for Plandome station on the Long Island Rail Road in New York.
  • A. PDM
    PDM is a modern Python package and dependency manager that emphasizes PEP 582 support and a streamlined, pyproject.toml-based workflow.
  • B. PTC
    PTC is an advanced safety system used on railroads to automatically prevent train collisions, overspeed derailments, and other dangerous movements.
  • C. PTC
    PTC is a Permanent Technical Committee, typically a standing expert group responsible for developing and maintaining technical standards or guidelines within a specific domain.
  • D. DPM
    DPM is the abbreviation for the División de Policía Militar, a military police division responsible for law enforcement and security duties within a nation's armed forces.
  • E. PMM
    PMM is the commonly used acronym for Perpignan Méditerranée Métropole, an intercommunal urban community centered on the city of Perpignan in southern France.
  • 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_69ca82e409348190a393777356b80a2a completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb5e64760819094f599f158d32f33 completed April 2, 2026, 12:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69d228f259b081909ce8a90ec1adad0d completed April 5, 2026, 9:18 a.m.
NEDg Description generation batch_69d22a78819481908ccff34730464f19 completed April 5, 2026, 9:25 a.m.
NED2 Entity disambiguation (via description) batch_69d22b0fea588190a4928c361c2367ca completed April 5, 2026, 9:27 a.m.
Created at: March 30, 2026, 8:44 p.m.