Triple

T6272685
Position Surface form Disambiguated ID Type / Status
Subject Kiel Life Science E140574 entity
Predicate hasAbbreviation P43 FINISHED
Object KLS E580351 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: KLS | Statement: [Kiel Life Science, hasAbbreviation, KLS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KLS
Context triple: [Kiel Life Science, hasAbbreviation, KLS]
  • A. KLS chosen
    KLS is a research center at Kiel University focused on interdisciplinary life science studies, including molecular biology, medicine, and environmental sciences.
  • B. KLSV
    KLSV is the ICAO airport code for Nellis Air Force Base, a major United States Air Force installation near Las Vegas, Nevada.
  • C. KLAL
    KLAL is the ICAO airport code for Lakeland Linder International Airport in Lakeland, Florida, a regional airport known for general aviation and cargo operations.
  • D. KLE
    KLE is the vehicle registration code for the district of Cleves (Kleve) in the German state of North Rhine-Westphalia.
  • E. KSL
    KSL is the primary sign language used by the Deaf community in South Korea, with its own distinct grammar and vocabulary separate from spoken Korean.
  • 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_69c008cabc4081909723e2547c9d6cc0 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063bca5488190b9da3c037cfc7953 completed March 22, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c519404dbc8190850f7874d2be51b5 completed March 26, 2026, 11:32 a.m.
Created at: March 22, 2026, 4:25 p.m.