Triple
T15656725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Double Cherry |
E376460
|
entity |
| Predicate | maximumCopiesInStandardPlay |
P119620
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Double Cherry, maximumCopiesInStandardPlay, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumCopiesInStandardPlay Context triple: [Double Cherry, maximumCopiesInStandardPlay, 5]
-
A.
usesMinimumCopiesPerCard
Indicates that there is a constraint specifying the minimum number of copies of each card that must be used or included in a given context.
-
B.
numberOfPlays
Indicates the total count of times an item, such as a track or media asset, has been played.
-
C.
gameCountMaximum
Indicates the maximum number of games allowed or recorded in a given context or relationship.
-
D.
numberOfKnownPlays
Indicates the total count of plays that are known to be associated with a given entity (such as an author, theater, or period).
-
E.
typicalNumberOfPlayers
Indicates the usual or standard number of players involved in participating in an activity or game.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ef1f83c8190bbf65eed162cbd55 |
completed | April 16, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69deda890140819082608931e993dd61 |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f3016c8190ac68d76e65e07af4 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:15 a.m.