Triple
T35301117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magic Weekend |
E1019505
|
entity |
| Predicate | typicalNumberOfMatches |
P206919
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [Magic Weekend, typicalNumberOfMatches, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNumberOfMatches Context triple: [Magic Weekend, typicalNumberOfMatches, 7]
-
A.
typicalNumberOfMatchesPerSeries
Indicates the usual or standard count of matches that are played within a single series.
-
B.
typicalMatchType
Indicates the usual or most common type of match or pairing that characterizes how two entities are related or aligned.
-
C.
typicalNumberOfSelections
Indicates the usual or expected count of selections made in a given choice or selection process.
-
D.
numberOfTestMatches
Indicates the total count of test matches associated with a given entity (such as a player, team, or series) in the relationship.
-
E.
typicalMatchRules
Indicates that two entities are considered a standard or default match according to predefined matching rules or criteria.
- 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_69f76de8b4c48190ae504b86185c474c |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0324d08190ac5b610cc0f6a38c |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82179081908325a59b8539b3a8 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.