Triple

T17434534
Position Surface form Disambiguated ID Type / Status
Subject USG E423966 entity
Predicate abbreviation P43 FINISHED
Object USG 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: USG | Statement: [USG, abbreviation, USG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: USG
Context triple: [USG, abbreviation, USG]
  • A. USG chosen
    USG is the acronym commonly used for the University System of Georgia, the public higher education system for the state of Georgia in the United States.
  • B. USG
    USG is a regional higher education center in Rockville, Maryland that hosts programs from multiple University System of Maryland institutions on a single shared campus.
  • C. UCG
    UCG is the official abbreviation for the University of Montenegro, the largest and most prominent public university in Montenegro.
  • D. USZ
    USZ is a major public teaching hospital in Zurich, Switzerland, affiliated with the University of Zurich and known for its advanced medical care and research.
  • E. USAR
    USAR is the commonly used abbreviation for the United States Army Reserve, the federal reserve force of the U.S. Army composed of part-time soldiers who support active-duty operations.
  • 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_69d889d88b6081908bada047f5b3ba51 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4490274608190a60ada9aeb246eff completed April 19, 2026, 3:16 a.m.
Created at: April 10, 2026, 5:46 a.m.