Triple

T1430571
Position Surface form Disambiguated ID Type / Status
Subject Code of Massachusetts Regulations E30434 entity
Predicate shortName P43 FINISHED
Object CMR
CMR is the commonly used abbreviation for the Code of Massachusetts Regulations, the official compilation of administrative rules and regulations issued by Massachusetts state agencies.
 E163697 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: CMR | Statement: [Code of Massachusetts Regulations, shortName, CMR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CMR
Context triple: [Code of Massachusetts Regulations, shortName, CMR]
  • A. CMR
    CMR is the three-letter FIFA country code used to represent the Cameroon national football team in international competitions and rankings.
  • B. CM
    CM is the post-nominal letters used to denote a Member of the Order of Canada, one of the country’s highest civilian honors.
  • C. CM
    CM is the two-letter ISO 3166-1 alpha-2 country code assigned to Cameroon.
  • D. SMR
    SMR is the three-letter ISO 3166-1 alpha-3 country code assigned to San Marino.
  • E. MRU
    MRU is the three-letter ISO 4217 currency code for the Mauritanian ouguiya, the official currency of Mauritania.
  • 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: CMR
Triple: [Code of Massachusetts Regulations, shortName, CMR]
Generated description
CMR is the commonly used abbreviation for the Code of Massachusetts Regulations, the official compilation of administrative rules and regulations issued by Massachusetts state agencies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CMR
Target entity description: CMR is the commonly used abbreviation for the Code of Massachusetts Regulations, the official compilation of administrative rules and regulations issued by Massachusetts state agencies.
  • A. CMR
    CMR is the three-letter FIFA country code used to represent the Cameroon national football team in international competitions and rankings.
  • B. CM
    CM is the post-nominal letters used to denote a Member of the Order of Canada, one of the country’s highest civilian honors.
  • C. CM
    CM is the two-letter ISO 3166-1 alpha-2 country code assigned to Cameroon.
  • D. SMR
    SMR is the three-letter ISO 3166-1 alpha-3 country code assigned to San Marino.
  • E. MRU
    MRU is the three-letter ISO 4217 currency code for the Mauritanian ouguiya, the official currency of Mauritania.
  • 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_69a498fc69ec8190b61722bd4b67c4d2 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c4dc3e2081909ff951fe73db277b completed March 1, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad016bf2608190a675cbd42e474082 completed March 8, 2026, 4:56 a.m.
NEDg Description generation batch_69ad0294353081908e29735d1b83f2cc completed March 8, 2026, 5:01 a.m.
NED2 Entity disambiguation (via description) batch_69ad02f6bf288190bcb785762d14787c completed March 8, 2026, 5:02 a.m.
Created at: March 1, 2026, 8 p.m.