Triple
T558531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Card Players |
E11996
|
entity |
| Predicate | hasVersionCount |
P16369
|
FINISHED |
| Object | multiple compositions with varying numbers of players |
—
|
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: multiple compositions with varying numbers of players | Statement: [The Card Players, hasVersionCount, multiple compositions with varying numbers of players]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVersionCount Context triple: [The Card Players, hasVersionCount, multiple compositions with varying numbers of players]
-
A.
hasVersionNumber
Indicates that an entity is associated with a specific version identifier or number.
-
B.
hasVersionToken
Indicates that an entity is associated with a specific version identifier or token that distinguishes one version of it from another.
-
C.
hasStandardVersion
Indicates that one entity serves as the official or canonical version of another entity.
-
D.
hasMonthCount
Indicates a relationship where an entity is associated with a specific number of months.
-
E.
hasVerseCount
Indicates that an entity (such as a text or section) is associated with a specific number of verses it contains.
- 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a499df43f08190b514a38d36fc271d |
completed | March 1, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69a494bd78e8819083c519669158f209 |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a4985952a481908b918350ececf484 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:32 p.m.