Triple

T5411763
Position Surface form Disambiguated ID Type / Status
Subject UNIL E121027 entity
Predicate abbreviation P43 FINISHED
Object UNIL E121027 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: UNIL | Statement: [UNIL, abbreviation, UNIL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UNIL
Context triple: [UNIL, abbreviation, UNIL]
  • A. UNIL chosen
    UNIL is the commonly used abbreviation for the University of Lausanne, a major public research university in Lausanne, Switzerland.
  • B. UNI
    UNI is a public university in Cedar Falls, Iowa, known for its strong teacher education programs and comprehensive undergraduate and graduate offerings.
  • C. Universia
    Universia is an Ibero-American university network and online platform that connects higher education institutions across Spanish- and Portuguese-speaking countries to promote collaboration, academic resources, and educational services.
  • D. UNISWA
    UNISWA is the commonly used acronym for the University of Swaziland, the national public university of Eswatini.
  • E. UNA
    UNA is the stock ticker symbol for Unilever, a major multinational consumer goods company known for its wide range of food, personal care, and household products.
  • 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_69bd463a41cc8190b32ff5af2b96ca93 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd87b9e578819086380ff18a633cb0 completed March 20, 2026, 5:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf33a22e188190861459f74c3f615a completed March 22, 2026, 12:11 a.m.
Created at: March 20, 2026, 2:05 p.m.