Triple

T2329083
Position Surface form Disambiguated ID Type / Status
Subject White Plains station E48358 entity
Predicate code P1537 FINISHED
Object WPN
WPN is the station code used to identify White Plains station in transportation and scheduling systems.
 E255907 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: WPN | Statement: [White Plains station, code, WPN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WPN
Context triple: [White Plains station, code, WPN]
  • A. WPK
    WPK is the ruling communist party of North Korea that dominates the country’s political system and state ideology.
  • B. WUN
    WUN is the vehicle registration code for the district of Wunsiedel im Fichtelgebirge in Upper Franconia, Germany.
  • C. WCP
    WCP is the abbreviation for the World Climate Programme, an international initiative focused on understanding and addressing global climate variability and change.
  • D. W8
    W8 is a central London postcode district covering the affluent Kensington area, known for its upscale residences, shops, and cultural institutions.
  • E. WZ
    WZ is the IATA airline designator assigned to Red Wings Airlines, a Russian passenger carrier.
  • 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: WPN
Triple: [White Plains station, code, WPN]
Generated description
WPN is the station code used to identify White Plains station in transportation and scheduling systems.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WPN
Target entity description: WPN is the station code used to identify White Plains station in transportation and scheduling systems.
  • A. WPK
    WPK is the ruling communist party of North Korea that dominates the country’s political system and state ideology.
  • B. WUN
    WUN is the vehicle registration code for the district of Wunsiedel im Fichtelgebirge in Upper Franconia, Germany.
  • C. WCP
    WCP is the abbreviation for the World Climate Programme, an international initiative focused on understanding and addressing global climate variability and change.
  • D. W8
    W8 is a central London postcode district covering the affluent Kensington area, known for its upscale residences, shops, and cultural institutions.
  • E. WZ
    WZ is the IATA airline designator assigned to Red Wings Airlines, a Russian passenger carrier.
  • 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_69a88aa308a88190b0b86c011fda7fce completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc665c6548190af90d70475b4519b completed March 7, 2026, 6:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae8974ab8c81908ec2bddcc882cf42 completed March 9, 2026, 8:48 a.m.
NEDg Description generation batch_69ae8a084b388190a6d79df8d94b236d completed March 9, 2026, 8:51 a.m.
NED2 Entity disambiguation (via description) batch_69ae8a895b6c8190bfd064742e3cc4f8 completed March 9, 2026, 8:53 a.m.
Created at: March 4, 2026, 7:50 p.m.