Triple
T18271227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NBC Sports Premier League coverage |
E437618
|
entity |
| Predicate | typicalMatchWindows |
P131119
|
FINISHED |
| Object | weekend matchdays |
—
|
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: weekend matchdays | Statement: [NBC Sports Premier League coverage, typicalMatchWindows, weekend matchdays]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalMatchWindows Context triple: [NBC Sports Premier League coverage, typicalMatchWindows, weekend matchdays]
-
A.
typicalMatchType
Indicates the usual or most common type of match or pairing that characterizes how two entities are related or aligned.
-
B.
typicalMatchRules
Indicates that two entities are considered a standard or default match according to predefined matching rules or criteria.
-
C.
typicalApplicationWindow
Indicates that something is a standard or commonly used application window in a software environment.
-
D.
typicalMaskType
Indicates the kind or category of mask that is most commonly or characteristically used or associated with an entity.
-
E.
matchType
Indicates the specific category or nature of how two or more entities correspond or align with each other within a given context.
- 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ff7e00548190a28916a696831336 |
completed | April 19, 2026, 4:14 p.m. |
| PD | Predicate disambiguation | batch_69e44fd81c788190b08c6be3b07a08c5 |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e451a0ba208190a5fe92832a8f7a49 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 10:34 a.m.