Triple

T5570870
Position Surface form Disambiguated ID Type / Status
Subject Unicode Collation Algorithm E146195 entity
Predicate identifier P3732 FINISHED
Object UTS #10 E146194 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: UTS #10 | Statement: [Unicode Collation Algorithm, identifier, UTS #10]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UTS #10
Context triple: [Unicode Collation Algorithm, identifier, UTS #10]
  • A. UTS #10 chosen
    UTS #10 is the Unicode Collation Algorithm standard that defines how to consistently compare and sort Unicode text across different languages and platforms.
  • B. UTS
    UTS is a highly selective independent secondary school affiliated with the University of Toronto, known for its strong academic programs and gifted education.
  • C. UTS
    UTS is a major Australian public research university in Sydney known for its industry-focused education and modern urban campus.
  • D. UTS Sport
    UTS Sport is the sporting organisation representing the University of Technology Sydney, coordinating its student and representative sports programs and facilities.
  • E. UTS Central
    UTS Central is a major contemporary teaching, learning, and student services hub on the University of Technology Sydney campus, known for its distinctive glass design and integration of library and collaborative spaces.
  • 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_69c008ffed108190a084602227af6157 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020502a288190af37f9ebb88fccae completed March 22, 2026, 5:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0284bb71881908c0ac4ea2a302327 completed March 22, 2026, 5:35 p.m.
Created at: March 22, 2026, 3:37 p.m.