Triple

T12726520
Position Surface form Disambiguated ID Type / Status
Subject Września E304121 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object PWR E431222 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: PWR | Statement: [Września, vehicleRegistrationCode, PWR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PWR
Context triple: [Września, vehicleRegistrationCode, PWR]
  • A. PWR
    PWR is a global interfaith organization that convenes leaders and followers of diverse religious and spiritual traditions to promote dialogue, understanding, and cooperation for peace and justice.
  • B. PWRR
    PWRR is a line infantry regiment of the British Army, known as the Princess of Wales's Royal Regiment.
  • C. PWr chosen
    PWr is the commonly used abbreviation for Wrocław University of Science and Technology, a major technical university in Wrocław, Poland.
  • D. PW
    PW is the commonly used nickname of P. W. Botha, the former South African prime minister and state president during the apartheid era.
  • E. PW
    PW is the commonly used abbreviation for the Warsaw University of Technology, one of Poland’s leading technical universities.
  • 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_69d7bdf084148190ab9d513dc0735af4 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96415ebe48190ae935bc3a9b00f65 completed April 10, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c884bd08190bf0022e8303a4987 completed May 2, 2026, 10:36 p.m.
Created at: April 9, 2026, 5:25 p.m.