Triple
T266526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Copa América Centenario 2016 matches |
E5741
|
entity |
| Predicate | numberOfGroups |
P8911
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Copa América Centenario 2016 matches, numberOfGroups, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGroups Context triple: [Copa América Centenario 2016 matches, numberOfGroups, 4]
-
A.
airGroupSize
Indicates the number of units or elements grouped together in an air-related context (such as aircraft in a formation or air assets in an operation).
-
B.
numberOfPositions
Indicates the total count of distinct positions or roles associated with a given entity.
-
C.
numberOfLevels
Indicates the total count of hierarchical layers, stages, or floors associated with an entity.
-
D.
numberOfKnownMembers
Indicates the count of members within a group or set whose identities are known or have been explicitly determined.
-
E.
branchCount
Indicates the number of branches associated with a given entity or structure.
- F. None of above. chosen
Provenance (4 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_69a2587daeb081909591b9d30f80a271 |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25d90bab48190b3ef97a451653b7f |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b6f60b081908fc6467800a8849e |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25c8ae480819094f6d1bb0a6d2eb2 |
completed | Feb. 28, 2026, 3:10 a.m. |
Created at: Feb. 28, 2026, 2:56 a.m.