Triple
T18215790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Florida Levin College of Law |
E436151
|
entity |
| Predicate | hasRankingStrength |
P130283
|
FINISHED |
| Object | tax law |
—
|
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: tax law | Statement: [University of Florida Levin College of Law, hasRankingStrength, tax law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRankingStrength Context triple: [University of Florida Levin College of Law, hasRankingStrength, tax law]
-
A.
hasRankingFactor
Indicates that one entity contributes as a factor to determining the ranking or ordered position of another entity.
-
B.
hasRankingUnit
Indicates that one entity is associated with a specific unit or scale used to express its ranking or ordered position.
-
C.
hasRankingCategory
Indicates that an entity is associated with a particular ranking category or tier within an ordered classification system.
-
D.
hasRankingDomain
Indicates that one entity is associated with a specific ranking domain within which its rank or position is evaluated.
-
E.
isRanked
Indicates that an entity has been assigned a position or level within an ordered hierarchy or comparative list.
- 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_69d8b9103a8081908bbb0836fef10efd |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e47765a081908d0bbca1245f89ba |
completed | April 19, 2026, 2:19 p.m. |
| PD | Predicate disambiguation | batch_69e4332155d88190b106d0dceb4554af |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f684e48190b38c64b58c518b6a |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:32 a.m.