Triple
T18344488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UAE Derby |
E439498
|
entity |
| Predicate | weightAssignment |
P6679
|
FINISHED |
| Object | set weights with allowances |
—
|
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: set weights with allowances | Statement: [UAE Derby, weightAssignment, set weights with allowances]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weightAssignment Context triple: [UAE Derby, weightAssignment, set weights with allowances]
-
A.
scoreAssignment
Indicates evaluating and assigning a grade or numerical score to an assignment.
-
B.
weightingMethod
chosen
Indicates how relative importance or influence is assigned to elements within a set, such as criteria, features, or data points, in a calculation or decision process.
-
C.
weightingFunction
Indicates a function that assigns relative importance or influence (weights) to elements within a set, often to adjust their impact in a calculation or decision process.
-
D.
sectorWeighting
Indicates the proportion or emphasis assigned to a particular sector within a broader portfolio, index, or classification.
-
E.
weight
Indicates a relationship where a numerical value quantifies how heavy an entity is, often used to measure or compare mass or load.
- 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_69d8b9175fec8190af865699b4e64d8c |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e514f2c8ec8190b045482846a68204 |
completed | April 19, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69e44fe91bc08190906518e1b120fcf0 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:37 a.m.