Triple
T3832518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European Car of the Year |
E91045
|
entity |
| Predicate | numberOfJurors |
P20930
|
FINISHED |
| Object | about 60 |
—
|
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: about 60 | Statement: [European Car of the Year, numberOfJurors, about 60]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfJurors Context triple: [European Car of the Year, numberOfJurors, about 60]
-
A.
hasNumberOfJurors
Indicates the relationship specifying how many jurors are associated with a given legal case, trial, or proceeding.
-
B.
numberOfJudges
Indicates the total count of judges associated with a particular case, event, or entity.
-
C.
minimumNumberOfJustices
Indicates the smallest number of justices required for a court or judicial body to validly conduct its proceedings or make decisions.
-
D.
usesJuries
Indicates that a legal system, court, or process employs juries to participate in deciding cases or determining outcomes.
-
E.
juryComposition
chosen
Indicates the relationship specifying how a jury is constituted, including the number, type, or characteristics of its members.
- 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_69aed960b538819096561c8ed448dec9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeb8787bc8190819a7af975b609df |
completed | March 9, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69aee74c2e04819094b94b3c0bac1806 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:17 p.m.