Triple

T8120507
Position Surface form Disambiguated ID Type / Status
Subject Sharif University of Technology E189594 entity
Predicate shortName P43 FINISHED
Object SUT E189594 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: SUT | Statement: [Sharif University of Technology, shortName, SUT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SUT
Context triple: [Sharif University of Technology, shortName, SUT]
  • A. SUT chosen
    SUT is the commonly used abbreviation for Sharif University of Technology, a leading science and engineering university in Iran.
  • B. SUS
    SUS is the commonly used abbreviation for the State University System of Florida, the network of public universities in the state of Florida.
  • C. SUS
    SUS is a standardized specification that defines the requirements for a compliant UNIX operating system, ensuring compatibility and interoperability across different UNIX implementations.
  • D. SIT
    SIT was the ISO 4217 currency code for the Slovenian tolar, the former national currency of Slovenia before adoption of the euro.
  • E. Susitnu
    Susitnu is the Indigenous (Dena’ina) name for Alaska’s Susitna River, a major waterway in south-central Alaska.
  • 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_69ca82bb74848190afb1f18640632c10 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4359f3dc8190a2330cf6efb8c084 completed March 31, 2026, 3:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc9454ccb48190b0f894bed5da8a01 completed April 1, 2026, 3:43 a.m.
Created at: March 30, 2026, 5:33 p.m.