Triple
T27885528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Checkers |
E705212
|
entity |
| Predicate | hasStartingPiecesPerPlayer |
P192277
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [Checkers, hasStartingPiecesPerPlayer, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStartingPiecesPerPlayer Context triple: [Checkers, hasStartingPiecesPerPlayer, 12]
-
A.
hasStandardDiceCountPerPlayer
Indicates that there is a specified, consistent number of dice allocated to each player in the context of a game or activity.
-
B.
hasLeadCountPerSide
Indicates the number of lead elements or units associated with each side in a given context or configuration.
-
C.
hasNumberOfBishops
Indicates the relationship that specifies how many bishops are associated with a given entity.
-
D.
usesStartingRowsPerPlayer
Indicates that the configuration or rule specifies a distinct number of starting rows allocated to each player.
-
E.
numberOfPieces
Indicates the quantity of discrete parts or units into which something is divided or composed.
- 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_69ef96b39c448190a9b3aa6672a5168f |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69fd05ba6b2c81909c62b46237d10365 |
completed | May 7, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69fd03039e48819082b6e12c5453885a |
completed | May 7, 2026, 9:24 p.m. |
| PDg | Predicate description generation | batch_69fd05b965608190a3666410b9f8e125 |
completed | May 7, 2026, 9:35 p.m. |
Created at: April 27, 2026, 6:32 p.m.