Triple
T681644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pontifical Catholic University of Chile |
E13194
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
UC
UC is a leading Chilean university, widely recognized for its academic excellence and strong influence in education, research, and public policy in Latin America.
|
E82391
|
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: UC | Statement: [Pontifical Catholic University of Chile, shortName, UC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UC Context triple: [Pontifical Catholic University of Chile, shortName, UC]
-
A.
UC
UC is a public university in Canberra, Australia, known for its career-focused programs and strong industry partnerships.
-
B.
CU
CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
-
C.
UGC
UGC (University Grants Commission) is a statutory body of the Indian government responsible for coordinating, determining, and maintaining standards of higher education in India.
-
D.
UA
UA is the two-letter IATA airline designator used worldwide to identify United Airlines on tickets, schedules, and flight information.
-
E.
UA
UA is a major public research university located in Tuscaloosa, Alabama, known for its strong academic programs and prominent Crimson Tide athletics.
- 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: UC Triple: [Pontifical Catholic University of Chile, shortName, UC]
Generated description
UC is a leading Chilean university, widely recognized for its academic excellence and strong influence in education, research, and public policy in Latin America.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: UC Target entity description: UC is a leading Chilean university, widely recognized for its academic excellence and strong influence in education, research, and public policy in Latin America.
-
A.
UC
UC is a public university in Canberra, Australia, known for its career-focused programs and strong industry partnerships.
-
B.
CU
CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
-
C.
UGC
UGC (University Grants Commission) is a statutory body of the Indian government responsible for coordinating, determining, and maintaining standards of higher education in India.
-
D.
UA
UA is the two-letter IATA airline designator used worldwide to identify United Airlines on tickets, schedules, and flight information.
-
E.
UA
UA is a major public research university located in Tuscaloosa, Alabama, known for its strong academic programs and prominent Crimson Tide athletics.
- 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_69a4933d3bf88190972041cd8cf143b9 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a06f9ee88190a2d757aacd8e3f5b |
completed | March 1, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5c3a5701c8190810e5e52bc2b61f7 |
completed | March 2, 2026, 5:06 p.m. |
| NEDg | Description generation | batch_69a5cd8acc888190b9bb80198bce5d00 |
completed | March 2, 2026, 5:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a5ce6232e08190a8dba769f173f431 |
completed | March 2, 2026, 5:52 p.m. |
Created at: March 1, 2026, 7:36 p.m.