Triple

T22240328
Position Surface form Disambiguated ID Type / Status
Subject KER E549700 entity
Predicate hasReutersInstrumentCode P120941 FINISHED
Object KER.PA 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: KER.PA | Statement: [KER, hasReutersInstrumentCode, KER.PA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KER.PA
Context triple: [KER, hasReutersInstrumentCode, KER.PA]
  • A. KER chosen
    KER is the stock ticker symbol for Kering, the French multinational luxury goods group that owns brands such as Gucci, Saint Laurent, and Bottega Veneta.
  • B. KP
    KP is the vehicle registration code used for the Sežana area in Slovenia.
  • C. KP
    KP is a subsystem of axiomatic set theory that omits the power set axiom and focuses on sets that are constructible via definable operations.
  • D. KP
    KP is the nickname of Kirk Penney, a New Zealand former professional basketball player known for his prolific scoring and international career.
  • E. KP
    KP is the commonly used abbreviation for Khyber Pakhtunkhwa, a province in northwestern Pakistan known for its mountainous terrain and diverse ethnic communities.
  • 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_69e11e4102b881909cf47d3768e25c19 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f132133b908190b0fb32a5ee68e1e6 completed April 28, 2026, 10:17 p.m.
Created at: April 16, 2026, 8:38 p.m.