Triple

T1204612
Position Surface form Disambiguated ID Type / Status
Subject Greater North Borneo languages E25858 entity
Predicate hasAbbreviation P43 FINISHED
Object GNB E64662 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: GNB | Statement: [Greater North Borneo languages, hasAbbreviation, GNB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GNB
Context triple: [Greater North Borneo languages, hasAbbreviation, GNB]
  • A. GNB chosen
    GNB is the commonly used abbreviation for the Good News Bible, a modern English translation of the Christian Bible known for its clear and simple language.
  • B. GN
    GN is a fast, meta-build system tool used primarily by the Chromium project to generate build files for Ninja.
  • C. GAB
    GAB is the three-letter ISO 3166-1 alpha-3 country code assigned to Gabon.
  • D. NKGB
    NKGB was a Soviet state security and intelligence agency that operated before the formation of the KGB, handling internal security, counterintelligence, and secret police functions.
  • E. GSB
    GSB is Stanford University's renowned graduate business school, offering MBA and other advanced management programs and known for its innovation, entrepreneurship focus, and global impact.
  • 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_69a4942b30f08190a91c60573e16b5ef completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bdc0f8d08190b340012a9eb26275 completed March 1, 2026, 10:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac7f3caed481908e9e4b6b9daa544d completed March 7, 2026, 7:40 p.m.
Created at: March 1, 2026, 7:46 p.m.