Triple

T2541502
Position Surface form Disambiguated ID Type / Status
Subject ALM (company) E57793 entity
Predicate hasAbbreviation P43 FINISHED
Object ALM E57793 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: ALM | Statement: [ALM (company), hasAbbreviation, ALM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ALM
Context triple: [ALM (company), hasAbbreviation, ALM]
  • A. ALM (company) chosen
    ALM (company) is a media and information services firm best known for publishing legal and business news, including leading industry rankings such as the Am Law 100.
  • B. ALP
    ALP is the commonly used abbreviation for Bolivia’s Plurinational Legislative Assembly, the country’s national bicameral legislature.
  • C. ALO
    ALO is the three-letter IATA airport code for Waterloo Regional Airport in Waterloo, Iowa, United States.
  • D. ALO
    ALO is the Arab Labor Organization, a specialized Arab League body that promotes labor standards, employment policies, and workers’ rights across Arab countries.
  • E. AELM
    AELM is the commonly used abbreviation for the APEC Economic Leaders' Meeting, an annual summit where leaders of Asia-Pacific economies discuss regional economic cooperation and policy.
  • 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_69ab4a5212d88190b989ce129f2ad87f completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd2bc7b5481908b3664495e99f1a4 completed March 7, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69af5d046430819095605b8a8fd987d5 completed March 9, 2026, 11:51 p.m.
Created at: March 6, 2026, 9:47 p.m.