Triple

T9177015
Position Surface form Disambiguated ID Type / Status
Subject University of North Georgia E220226 entity
Predicate nickname P55 FINISHED
Object UNG
UNG is a public university in Georgia known for its strong focus on leadership development, military programs, and accessible undergraduate education across multiple campuses.
 E782308 NE FINISHED

How this triple was built (4 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: UNG | Statement: [University of North Georgia, nickname, UNG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UNG
Context triple: [University of North Georgia, nickname, UNG]
  • A. UG
    UG is the ISO 3166-1 alpha-2 country code for Uganda, used in international standards and country abbreviations.
  • B. Ug
    Ug is a shape-shifting intergalactic bounty hunter featured in the sci-fi horror comedy film "Critters 2: The Main Course."
  • C. UNT
    UNT is the commonly used acronym for the National University of Trujillo, a public higher education institution in Trujillo, Peru.
  • D. OUN
    OUN is the National Weather Service forecast office identifier for the Norman, Oklahoma weather forecast and warning center.
  • E. GU
    GU is the two-letter ISO 3166 country code assigned to Guam, an unincorporated territory of the United States in the western Pacific Ocean.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: UNG
Triple: [University of North Georgia, nickname, UNG]
Generated description
UNG is a public university in Georgia known for its strong focus on leadership development, military programs, and accessible undergraduate education across multiple campuses.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UNG
Target entity description: UNG is a public university in Georgia known for its strong focus on leadership development, military programs, and accessible undergraduate education across multiple campuses.
  • A. UG
    UG is the ISO 3166-1 alpha-2 country code for Uganda, used in international standards and country abbreviations.
  • B. Ug
    Ug is a shape-shifting intergalactic bounty hunter featured in the sci-fi horror comedy film "Critters 2: The Main Course."
  • C. UNT
    UNT is the commonly used acronym for the National University of Trujillo, a public higher education institution in Trujillo, Peru.
  • D. OUN
    OUN is the National Weather Service forecast office identifier for the Norman, Oklahoma weather forecast and warning center.
  • E. GU
    GU is the two-letter ISO 3166 country code assigned to Guam, an unincorporated territory of the United States in the western Pacific Ocean.
  • F. None of above. chosen

Provenance (5 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_69ca83e589948190ac9907819db11ddf completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccbfa60c3c8190b6335b9067de5b72 completed April 1, 2026, 6:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d054a87f3881908bda69238d2b97ab completed April 4, 2026, midnight
NEDg Description generation batch_69d0568634848190b5a2db2f7d3759f8 completed April 4, 2026, 12:08 a.m.
NED2 Entity disambiguation (via description) batch_69d05717b6588190a92ded4f745d133a completed April 4, 2026, 12:11 a.m.
Created at: March 30, 2026, 7:23 p.m.