Triple
T35862257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ganjifa playing cards |
E1036983
|
entity |
| Predicate | suitSystem |
P183915
|
FINISHED |
| Object | Mughal Ganjifa |
—
|
NE NERFINISHED |
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: Mughal Ganjifa | Statement: [Ganjifa playing cards, suitSystem, Mughal Ganjifa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: suitSystem Context triple: [Ganjifa playing cards, suitSystem, Mughal Ganjifa]
-
A.
suit
Indicates that one entity is appropriate, fitting, or satisfactory for another entity or a particular purpose or situation.
-
B.
suitType
Indicates the specific category or style of suit associated with an entity (e.g., business suit, spacesuit, wetsuit).
-
C.
suitProperties
Indicates that certain properties or characteristics are appropriate, compatible, or well-matched to a given entity or context.
-
D.
suitColor
Indicates that one entity has or is associated with a particular color of suit.
-
E.
matchSystem
Indicates a relationship where an entity is paired or aligned with a particular system according to defined matching 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_69f76e1d279c8190843e5b64a0a12c3f |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aaabb58c8190bf81673608ecfb6e |
completed | May 3, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d435288190b30b1991fb003121 |
completed | May 3, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f7aa33e0488190a135166bb67e1118 |
completed | May 3, 2026, 8:04 p.m. |
Created at: May 3, 2026, 4:06 p.m.