Triple
T9492419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Guanajuato |
E228922
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
UG
UG is the commonly used abbreviation for the University of Guanajuato, a major public higher education institution in the Mexican state of Guanajuato.
|
E801894
|
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: UG | Statement: [University of Guanajuato, shortName, UG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UG Context triple: [University of Guanajuato, shortName, UG]
-
A.
UG
UG is the ISO 3166-1 alpha-2 country code for Uganda, used in international standards and country abbreviations.
-
B.
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.
-
C.
Ug
Ug is a shape-shifting intergalactic bounty hunter featured in the sci-fi horror comedy film "Critters 2: The Main Course."
-
D.
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.
-
E.
GU
GU is a United Kingdom postcode area covering Guildford and surrounding parts of Surrey and nearby counties.
- 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: UG Triple: [University of Guanajuato, shortName, UG]
Generated description
UG is the commonly used abbreviation for the University of Guanajuato, a major public higher education institution in the Mexican state of Guanajuato.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: UG Target entity description: UG is the commonly used abbreviation for the University of Guanajuato, a major public higher education institution in the Mexican state of Guanajuato.
-
A.
UG
UG is the ISO 3166-1 alpha-2 country code for Uganda, used in international standards and country abbreviations.
-
B.
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.
-
C.
Ug
Ug is a shape-shifting intergalactic bounty hunter featured in the sci-fi horror comedy film "Critters 2: The Main Course."
-
D.
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.
-
E.
GU
GU is a United Kingdom postcode area covering Guildford and surrounding parts of Surrey and nearby counties.
- 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_69ca847424f081908180305555139f7a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd80ca26bc819084add20027aea4a5 |
completed | April 1, 2026, 8:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d12d27c0808190baf5ae04a1b915bb |
completed | April 4, 2026, 3:24 p.m. |
| NEDg | Description generation | batch_69d12da44d7c8190afb11ae3009a79e5 |
completed | April 4, 2026, 3:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d12e1459348190aed583b2364a53dd |
completed | April 4, 2026, 3:28 p.m. |
Created at: March 30, 2026, 7:56 p.m.