Triple
T16960862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Copa América 1957 matches |
E411422
|
entity |
| Predicate | usesSubstitutions |
P111505
|
FINISHED |
| Object | limited |
—
|
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: limited | Statement: [Copa América 1957 matches, usesSubstitutions, limited]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesSubstitutions Context triple: [Copa América 1957 matches, usesSubstitutions, limited]
-
A.
hasSubstitutionsType
chosen
Indicates that an entity is associated with a specific kind or category of substitutions applied to it or occurring within it.
-
B.
involvesSubstitute
Indicates that one entity participates in a situation, event, or role as a replacement or stand-in for another entity.
-
C.
numberOfSubstitutes
Indicates the quantity of substitute entities associated with or allowed for a given entity or situation.
-
D.
usesTransformation
Indicates that one entity applies or relies on a specific transformation process, method, or function to operate on or convert another entity.
-
E.
isUsedUnder
Indicates that one entity is utilized or applied within the context, conditions, or framework defined by another entity.
- 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_69d886c9c9d481909afe222093641cae |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d0209a9081909d9c62456bc16e14 |
completed | April 18, 2026, 6:40 p.m. |
| PD | Predicate disambiguation | batch_69e32b9cddf88190bc42709604047353 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:31 a.m.