Triple

T26439163
Position Surface form Disambiguated ID Type / Status
Subject Pittsburgh and West Virginia Railway E665036 entity
Predicate railroadReportingMarks P18202 FINISHED
Object P&WV
P&WV is the reporting mark used for the Pittsburgh and West Virginia Railway, a regional railroad that operated in the Appalachian area of the United States.
 E1726637 NE FINISHED

How this triple was built (3 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: P&WV | Statement: [Pittsburgh and West Virginia Railway, railroadReportingMarks, P&WV]
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: P&WV
Triple: [Pittsburgh and West Virginia Railway, railroadReportingMarks, P&WV]
Generated description
P&WV is the reporting mark used for the Pittsburgh and West Virginia Railway, a regional railroad that operated in the Appalachian area of the United States.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: railroadReportingMarks
Context triple: [Pittsburgh and West Virginia Railway, railroadReportingMarks, P&WV]
  • A. usesRollingStockBrand
    Indicates that one entity employs or operates rolling stock manufactured under a specific brand.
  • B. railCarries
    Indicates that a rail or railway system transports or conveys a specified entity from one place to another.
  • C. railroadCodeFor chosen
    Indicates that a specific railroad code is assigned to or used to identify a particular railroad entity.
  • D. railcode
    Indicates that an entity is associated with a specific railway code used for identification or classification within a rail system.
  • E. railroadClass
    Indicates the classification or category of a railroad according to an established system (e.g., by size, revenue, or regulatory status).
  • F. None of above.

Provenance (6 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_69ee883c851881909e2ab04efbb3c5fe completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f621fcea1481909b6f8b3af1ee6820 completed May 2, 2026, 4:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11aecdb59881908ea101f3d86d0f34 completed May 23, 2026, 1:42 p.m.
NEDg Description generation batch_6a11b2c94adc819094e6b7ce0087d8e0 completed May 23, 2026, 1:59 p.m.
NED2 Entity disambiguation (via description) batch_6a11b33845e8819091d97a8198007f76 completed May 23, 2026, 2:01 p.m.
PD Predicate disambiguation batch_69f620debeb48190b7db395fb86cf8d9 completed May 2, 2026, 4:05 p.m.
Created at: April 26, 2026, 11:56 p.m.