Triple

T9077764
Position Surface form Disambiguated ID Type / Status
Subject Merrick station E217530 entity
Predicate code P1537 FINISHED
Object MRK
MRK is the station code for Merrick, a Long Island Rail Road commuter rail station in Merrick, New York.
 E776776 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: MRK | Statement: [Merrick station, code, MRK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MRK
Context triple: [Merrick station, code, MRK]
  • A. MRK
    MRK is the stock ticker symbol for Merck & Co., a major global pharmaceutical company known for developing prescription medicines, vaccines, and animal health products.
  • B. MR
    MR is a Belgian French-speaking liberal political party that participated as one of the partners in the federal Vivaldi coalition government led by Alexander De Croo.
  • C. MR
    MR is the official vehicle registration code used on license plates for the city of Marburg in the German state of Hesse.
  • D. MK
    MK is the postal area code designation for Milton Keynes and its surrounding region in the United Kingdom.
  • E. MK
    MK is the commonly used abbreviation for Umkhonto we Sizwe, the former armed wing of South Africa’s African National Congress during the anti-apartheid struggle.
  • 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: MRK
Triple: [Merrick station, code, MRK]
Generated description
MRK is the station code for Merrick, a Long Island Rail Road commuter rail station in Merrick, New York.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MRK
Target entity description: MRK is the station code for Merrick, a Long Island Rail Road commuter rail station in Merrick, New York.
  • A. MRK
    MRK is the stock ticker symbol for Merck & Co., a major global pharmaceutical company known for developing prescription medicines, vaccines, and animal health products.
  • B. MR
    MR is a Belgian French-speaking liberal political party that participated as one of the partners in the federal Vivaldi coalition government led by Alexander De Croo.
  • C. MR
    MR is the official vehicle registration code used on license plates for the city of Marburg in the German state of Hesse.
  • D. MK
    MK is the postal area code designation for Milton Keynes and its surrounding region in the United Kingdom.
  • E. MK
    MK is the commonly used abbreviation for Umkhonto we Sizwe, the former armed wing of South Africa’s African National Congress during the anti-apartheid struggle.
  • 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_69ca83d6c14c8190bc056d927f00a2a2 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc95c7d3688190a4c1c6a92965eae4 completed April 1, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69cffe190c28819098ee017c75d72ad0 completed April 3, 2026, 5:51 p.m.
NEDg Description generation batch_69d0013b50e081909595efe822bf5565 completed April 3, 2026, 6:04 p.m.
NED2 Entity disambiguation (via description) batch_69d001f04db48190aaa1fb9efb36df2b completed April 3, 2026, 6:07 p.m.
Created at: March 30, 2026, 7:12 p.m.