Triple
T36508766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IRB World Rankings |
E899840
|
entity |
| Predicate | rankingScale |
P16725
|
FINISHED |
| Object | open-ended rating points scale |
—
|
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: open-ended rating points scale | Statement: [IRB World Rankings, rankingScale, open-ended rating points scale]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankingScale Context triple: [IRB World Rankings, rankingScale, open-ended rating points scale]
-
A.
rankingScope
Indicates the context or domain within which a ranking is defined, interpreted, or applied.
-
B.
rankingPoints
Indicates the number of points assigned to an entity based on its position or performance in a ranking or competition.
-
C.
rankGrade
Indicates the grade or level assigned to an entity within a ranking or evaluation system.
-
D.
rankingType
Indicates the specific basis or method by which items are ordered or ranked relative to one another.
-
E.
scoreScale
chosen
Indicates the scale or range on which a score or rating is expressed or measured.
- 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_69f76e5dada881909da2d34bc7a9202a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
Created at: May 3, 2026, 4:10 p.m.