Triple

T11096592
Position Surface form Disambiguated ID Type / Status
Subject eu-LISA E262393 entity
Predicate managesSystem P76502 FINISHED
Object SIS E719084 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: SIS | Statement: [eu-LISA, managesSystem, SIS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SIS
Context triple: [eu-LISA, managesSystem, SIS]
  • A. SIS
    SIS is the commonly used abbreviation for the United Kingdom’s Secret Intelligence Service, the foreign intelligence agency often referred to as MI6.
  • B. SIS
    SIS is the CERN Scientific Information Service, responsible for managing and providing access to the organization’s scientific publications, data, and library resources.
  • C. SIS II chosen
    SIS II (Schengen Information System II) is a large-scale European database that supports border control, law enforcement, and security cooperation among Schengen Area countries by sharing alerts on persons and objects.
  • D. Sis
    Sis was the medieval capital city of the Armenian Kingdom of Cilicia, serving as its political and cultural center.
  • E. Sis
    Sis is a Turkish film written and directed by Zülfü Livaneli that explores political repression and personal trauma in the aftermath of the 1980 military coup in Turkey.
  • 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_69d6aa9a40d88190a373e2c7e48285db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79a0a02cc8190a15df663d4860163 completed April 9, 2026, 12:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3e7eca9bc8190b43bae081d97d804 completed April 18, 2026, 8:22 p.m.
Created at: April 8, 2026, 9:27 p.m.