Triple

T19337221
Position Surface form Disambiguated ID Type / Status
Subject ML Update E483652 entity
Predicate hasAbbreviation P43 FINISHED
Object MLU NE NERFINISHED

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: MLU | Statement: [ML Update, hasAbbreviation, MLU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MLU
Context triple: [ML Update, hasAbbreviation, MLU]
  • A. MLU chosen
    MLU is the IATA airport code for Monroe Regional Airport, a public airport serving Monroe, Louisiana, in the United States.
  • B. MLN
    MLN is the IATA airport code for Melilla Airport, which serves the Spanish autonomous city of Melilla on the north coast of Africa.
  • C. MMLP
    MMLP is the ICAO airport code for Manuel Márquez de León International Airport serving La Paz, Baja California Sur, Mexico.
  • D. MMLM
    MMLM is the ICAO airport code for Los Mochis International Airport in Sinaloa, Mexico.
  • E. MMLT
    MMLT is the ICAO airport code for Loreto International Airport in Loreto, Baja California Sur, Mexico.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d244f8819080eb1f3491300db2 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e61646e89081908c9f1d2cf557672c completed April 20, 2026, 12:04 p.m.
Created at: April 10, 2026, 1:33 p.m.