Triple

T6847948
Position Surface form Disambiguated ID Type / Status
Subject Universidad Autónoma de Santo Domingo E157942 entity
Predicate abbreviation P43 FINISHED
Object UASD E623511 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: UASD | Statement: [Universidad Autónoma de Santo Domingo, abbreviation, UASD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UASD
Context triple: [Universidad Autónoma de Santo Domingo, abbreviation, UASD]
  • A. UASD chosen
    UASD is the Autonomous University of Santo Domingo, the oldest university in the Americas and the main public higher education institution in the Dominican Republic.
  • B. UCA
    UCA is a Jesuit-run Central American University in Managua, Nicaragua, known for its strong emphasis on social justice, human rights, and critical scholarship.
  • C. UCA
    UCA is a French public university located in Clermont-Ferrand, known for its research and education across disciplines such as science, health, law, and humanities.
  • D. UCA
    UCA is a Spanish public university based in Cádiz, known for its programs in marine sciences, engineering, and humanities.
  • E. UCA
    UCA is the Unicode Collation Algorithm, a Unicode standard that defines a language-independent method for ordering and comparing Unicode text.
  • 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_69c6882ed4c081909dc465a7cf8838be completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d7ce3e7481908e0472b8faafa473 completed March 27, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7427825d881909f151ca2ce3bd546 completed March 28, 2026, 2:52 a.m.
Created at: March 27, 2026, 2:20 p.m.