Triple

T7535142
Position Surface form Disambiguated ID Type / Status
Subject Rockville station E178129 entity
Predicate hasStationCode P1289 FINISHED
Object RKV (MARC)
RKV (MARC) is the station code used by the Maryland Area Regional Commuter (MARC) train service for Rockville station in Rockville, Maryland.
 E670974 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: RKV (MARC) | Statement: [Rockville station, hasStationCode, RKV (MARC)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: RKV (MARC)
Context triple: [Rockville station, hasStationCode, RKV (MARC)]
  • A. RKV
    RKV is the IATA airport code for Reykjavík Airport, the main domestic and regional airport serving Iceland’s capital city.
  • B. RKA
    RKA is the Russian Space Agency that managed Russia’s human spaceflight activities, including operations of the Mir space station.
  • C. RKC
    RKC is the commonly used abbreviation for the Revised Kyoto Convention, an international agreement that standardizes and simplifies customs procedures worldwide.
  • D. RKR
    RKR is the vehicle registration code assigned to vehicles registered in the Rymanów area of Poland.
  • E. MARC
    MARC is a regional planning and coordination agency serving the Kansas City metropolitan area, focusing on transportation, emergency services, environmental planning, and community development.
  • 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: RKV (MARC)
Triple: [Rockville station, hasStationCode, RKV (MARC)]
Generated description
RKV (MARC) is the station code used by the Maryland Area Regional Commuter (MARC) train service for Rockville station in Rockville, Maryland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: RKV (MARC)
Target entity description: RKV (MARC) is the station code used by the Maryland Area Regional Commuter (MARC) train service for Rockville station in Rockville, Maryland.
  • A. RKV
    RKV is the IATA airport code for Reykjavík Airport, the main domestic and regional airport serving Iceland’s capital city.
  • B. RKA
    RKA is the Russian Space Agency that managed Russia’s human spaceflight activities, including operations of the Mir space station.
  • C. RKC
    RKC is the commonly used abbreviation for the Revised Kyoto Convention, an international agreement that standardizes and simplifies customs procedures worldwide.
  • D. RKR
    RKR is the vehicle registration code assigned to vehicles registered in the Rymanów area of Poland.
  • E. MARC
    MARC is a commuter rail service in Maryland that connects Washington, D.C. with Baltimore and other regional destinations.
  • 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_69c69f2acdbc8190b5a8320168c1d0ba completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f84c13208190971096a0b81b0ff2 completed March 27, 2026, 9:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84f0c02148190bb5f63cf9891ec0c completed March 28, 2026, 9:58 p.m.
NEDg Description generation batch_69c84f9ce82081908813a1185b9b3570 completed March 28, 2026, 10:01 p.m.
NED2 Entity disambiguation (via description) batch_69c8500e64788190b196988290aea7d7 completed March 28, 2026, 10:02 p.m.
Created at: March 27, 2026, 3:47 p.m.