Triple

T10540832
Position Surface form Disambiguated ID Type / Status
Subject Neumünster E248689 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object NMS
NMS is the vehicle registration code for the city of Neumünster in Germany.
 E870999 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: NMS | Statement: [Neumünster, vehicleRegistrationCode, NMS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: NMS
Context triple: [Neumünster, vehicleRegistrationCode, NMS]
  • A. NMS
    NMS is the commonly used abbreviation for NOVA Medical School, a medical faculty of NOVA University Lisbon in Portugal.
  • B. NSM
    NSM was the stock ticker symbol for National Semiconductor, a former American semiconductor manufacturer known for its analog and mixed-signal integrated circuits.
  • C. NSM
    NSM is the commonly used abbreviation for the College of Natural Sciences and Mathematics, an academic division focused on education and research in scientific and mathematical disciplines.
  • D. Nims
    Nims is a company operating under the Italian coffee brand Lavazza, likely involved in coffee-related products or services within its corporate group.
  • E. Reg NMS
    Reg NMS is a set of U.S. Securities and Exchange Commission rules designed to modernize and strengthen the regulation and structure of the national equity securities markets.
  • 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: NMS
Triple: [Neumünster, vehicleRegistrationCode, NMS]
Generated description
NMS is the vehicle registration code for the city of Neumünster in Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: NMS
Target entity description: NMS is the vehicle registration code for the city of Neumünster in Germany.
  • A. NMS
    NMS is the commonly used abbreviation for NOVA Medical School, a medical faculty of NOVA University Lisbon in Portugal.
  • B. NSM
    NSM was the stock ticker symbol for National Semiconductor, a former American semiconductor manufacturer known for its analog and mixed-signal integrated circuits.
  • C. NSM
    NSM is the commonly used abbreviation for the College of Natural Sciences and Mathematics, an academic division focused on education and research in scientific and mathematical disciplines.
  • D. Nims
    Nims is a company operating under the Italian coffee brand Lavazza, likely involved in coffee-related products or services within its corporate group.
  • E. Reg NMS
    Reg NMS is a set of U.S. Securities and Exchange Commission rules designed to modernize and strengthen the regulation and structure of the national equity securities markets.
  • 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_69d381c733c08190ab1dd6239f5f34ae completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d50a582be48190856c6f272eea4dcf completed April 7, 2026, 1:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69d9341d96c08190a6ba644b9acfe2c8 completed April 10, 2026, 5:32 p.m.
NEDg Description generation batch_69d93802a4488190aa86ae209650d4e7 completed April 10, 2026, 5:48 p.m.
NED2 Entity disambiguation (via description) batch_69d938fcc3c48190a4acaaf75c1aa304 completed April 10, 2026, 5:53 p.m.
Created at: April 6, 2026, 12:32 p.m.