Triple
T10872907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UCE |
E256702
|
entity |
| Predicate | isOneOfMostImportantUniversitiesInCountry |
P96166
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [UCE, isOneOfMostImportantUniversitiesInCountry, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOneOfMostImportantUniversitiesInCountry Context triple: [UCE, isOneOfMostImportantUniversitiesInCountry, true]
-
A.
isOneOfLargestUniversitiesIn
Indicates that an institution ranks among the largest universities within a specified region or group.
-
B.
isLargestUniversityIn
Indicates that a university has the greatest size (e.g., by enrollment, area, or another defined metric) compared to all other universities within a specified region or group.
-
C.
isLargestFacultyOf
Indicates that one faculty is the largest (typically by size, number of members, or resources) among all faculties within a given institution or context.
-
D.
isLargestTechnicalUniversityIn
Indicates that a university is the largest technical university within a specified region or group.
-
E.
isLargestCampusOf
Indicates that one campus is the largest (by size, area, or capacity) among all campuses belonging to a particular institution or organization.
- F. None of above. chosen
Provenance (4 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_69d6aa848804819081b2713ca0bedf06 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d751885b348190baf6eb606089a438 |
completed | April 9, 2026, 7:13 a.m. |
| PD | Predicate disambiguation | batch_69d70d360c388190a3d829fe8862434f |
completed | April 9, 2026, 2:21 a.m. |
| PDg | Predicate description generation | batch_69d7101c96708190808fef73199e8482 |
completed | April 9, 2026, 2:34 a.m. |
Created at: April 8, 2026, 9:21 p.m.