Triple
T29710261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France vs Australia |
E751758
|
entity |
| Predicate | VARUsedFor |
P98
|
FINISHED |
| Object | penalty awarded to France |
—
|
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: penalty awarded to France | Statement: [France vs Australia, VARUsedFor, penalty awarded to France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: VARUsedFor Context triple: [France vs Australia, VARUsedFor, penalty awarded to France]
-
A.
usesVAR
Indicates that one entity makes use of, employs, or utilizes another entity as a variable or resource in performing some function or operation.
-
B.
usedFor
chosen
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
C.
usedByFor
Indicates that one entity makes use of another entity for a specific purpose or function.
-
D.
isUsedAs
Indicates that one entity serves a particular function, role, or purpose as another entity.
-
E.
usedInArgumentFor
Indicates that something (such as a statement, piece of evidence, or concept) is employed as support within an argument advocating for a particular claim or position.
- 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_69f0d62748848190b030d0a703629a7d |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f672d8463481909f9144dbfa8be162 |
completed | May 2, 2026, 9:55 p.m. |
| PD | Predicate disambiguation | batch_69f6659f246081909821c5f452d14e8f |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 7:30 p.m.