Triple

T3933100
Position Surface form Disambiguated ID Type / Status
Subject Braintree, Essex, England E90840 entity
Predicate hasPostcodeArea P920 FINISHED
Object CM E286818 NE FINISHED

How this triple was built (2 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: CM | Statement: [Braintree, Essex, England, hasPostcodeArea, CM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CM
Context triple: [Braintree, Essex, England, hasPostcodeArea, CM]
  • A. 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.
  • B. CM
    CM is the two-letter ISO 3166-1 alpha-2 country code assigned to Cameroon.
  • C. CM
    CM is the commonly used abbreviation for the Committee of Ministers, the decision-making body of the Council of Europe composed of the foreign ministers of member states or their representatives.
  • D. CM chosen
    CM is the postcode area in the United Kingdom that covers Chelmsford and surrounding parts of Essex.
  • E. CM
    CM is the standard abbreviation for "Concrete Mathematics," a well-known textbook by Graham, Knuth, and Patashnik that blends discrete mathematics with concrete problem-solving techniques.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69aed95f26e0819094b0e71974543a19 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeedcab1808190bf653f29062cdddb completed March 9, 2026, 3:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69b52887d4a48190b51df3f51ff197c0 completed March 14, 2026, 9:21 a.m.
Created at: March 9, 2026, 3:23 p.m.