Triple
T31358758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Countess |
E799805
|
entity |
| Predicate | hasCardAssociation |
P197058
|
FINISHED |
| Object | queen of spades |
—
|
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: queen of spades | Statement: [The Countess, hasCardAssociation, queen of spades]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCardAssociation Context triple: [The Countess, hasCardAssociation, queen of spades]
-
A.
hasCredit
Indicates that an entity possesses or is assigned a credit, such as financial credit, academic credit, or acknowledgment for a contribution.
-
B.
hasCreditCardVariant
Indicates that one credit card is a specific version, type, or variation of another credit card.
-
C.
hasAssociateMember
Indicates that an entity has another entity connected to it in a non-full, typically limited or secondary, membership capacity.
-
D.
hadCoBrandedCreditCardsWith
Indicates that two entities jointly issued or partnered on one or more co-branded credit card products.
-
E.
hasPhysicalCard
Indicates that an entity possesses or is associated with a tangible, real-world card object.
- 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_69f224e5e9bc8190a16339328897c4f8 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe766490c081908c49c8cc07d0ae9b |
completed | May 8, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69fe75bb5f4481908572a5ffcbdc5154 |
completed | May 8, 2026, 11:46 p.m. |
| PDg | Predicate description generation | batch_69fe7663b5bc81909524c40d3a172512 |
completed | May 8, 2026, 11:48 p.m. |
Created at: April 29, 2026, 9:17 p.m.