Triple
T1443313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Copa MX |
E31121
|
entity |
| Predicate | matchResolution |
P7241
|
FINISHED |
| Object | penalty shoot-out after draw in knockout phase |
—
|
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 shoot-out after draw in knockout phase | Statement: [Copa MX, matchResolution, penalty shoot-out after draw in knockout phase]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: matchResolution Context triple: [Copa MX, matchResolution, penalty shoot-out after draw in knockout phase]
-
A.
matchType
Indicates the specific category or nature of how two or more entities correspond or align with each other within a given context.
-
B.
matches
Indicates that two entities correspond to or are in agreement with each other according to some defined criteria or pattern.
-
C.
decidingMatchFor
Indicates a relationship where one entity is chosen or determined as the appropriate or final match for another entity among possible alternatives.
-
D.
typicalMatchType
Indicates the usual or most common type of match or pairing that characterizes how two entities are related or aligned.
-
E.
resolutionClass
chosen
Indicates the category or type of resolution applied to address or conclude a particular issue, conflict, or process.
- 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_69a4991633388190a4d61b5a98aa407a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c55714588190a95b4f677c21cbaa |
completed | March 1, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69a4c47a840c819083307a65c027a19e |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.