Triple

T19581408
Position Surface form Disambiguated ID Type / Status
Subject EEPU E489993 entity
Predicate hasIcaoCode P419 FINISHED
Object EEPU 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: EEPU | Statement: [EEPU, hasIcaoCode, EEPU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: EEPU
Context triple: [EEPU, hasIcaoCode, EEPU]
  • A. EEPU chosen
    EEPU is the ICAO airport code for the Port of Tallinn’s associated airfield in Estonia.
  • B. EPU
    EPU is the three-letter station code used by Transport for London to identify East Putney tube station on the London Underground network.
  • C. UEEE
    UEEE is the ICAO airport code for Yakutsk Airport, a major air transport hub in the Sakha Republic of Russia.
  • D. EPE
    EPE is a major expressway in India that serves as a peripheral bypass around Delhi to reduce traffic congestion and pollution in the National Capital Region.
  • E. EEUM
    EEUM is the engineering school of the University of Minho in Portugal, offering education and research across multiple engineering disciplines.
  • 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_69d8e8dd9374819098e36349b3211663 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e640281b7c8190be44268a58df058f completed April 20, 2026, 3:03 p.m.
Created at: April 10, 2026, 1:42 p.m.