Triple
T15481757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Bordeaux |
E376933
|
entity |
| Predicate | hasQSWorldRankingCategory |
P12314
|
FINISHED |
| Object | top 500 universities worldwide |
—
|
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: top 500 universities worldwide | Statement: [University of Bordeaux, hasQSWorldRankingCategory, top 500 universities worldwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasQSWorldRankingCategory Context triple: [University of Bordeaux, hasQSWorldRankingCategory, top 500 universities worldwide]
-
A.
hasQSAsiaRanking
Indicates that an entity is associated with a specific position or score in the QS Asia university rankings.
-
B.
hasRankingCategory
chosen
Indicates that an entity is associated with a particular ranking category or tier within an ordered classification system.
-
C.
hasWorldRankingPoints
Indicates that an entity possesses a certain number of points in a global or international ranking system.
-
D.
hasRankCategory
Indicates that an entity is assigned to a particular rank-based classification or level within an ordered hierarchy.
-
E.
hasOfficialRankingWeight
Indicates that something carries an officially recognized weight or importance in determining a ranking or ordered list.
- F. None of above.
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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f8cb4388190a3b4c92c3bb4ad4f |
completed | April 16, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69ded2874b788190999158e0f043be21 |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:34 a.m.