Triple
T34728484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hermann (The Queen of Spades) |
E1001136
|
entity |
| Predicate | mistakesFor |
P49451
|
FINISHED |
| Object | queen of spades instead of ace |
—
|
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 instead of ace | Statement: [Hermann (The Queen of Spades), mistakesFor, queen of spades instead of ace]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mistakesFor Context triple: [Hermann (The Queen of Spades), mistakesFor, queen of spades instead of ace]
-
A.
misinterpretedBy
Indicates that something (such as a statement, action, or signal) is understood incorrectly or in a way not intended by a particular entity.
-
B.
misidentifiedAs
chosen
Indicates that one entity has been incorrectly recognized, labeled, or understood as another, distinct entity.
-
C.
oftenConfusedWith
Indicates that one entity is frequently mistaken for or thought to be another due to similarity or ambiguity.
-
D.
associatedWithMisidentificationOf
Indicates a relationship where one entity is connected to, or involved in, the incorrect identification or labeling of another entity.
-
E.
reasonForMisidentification
Indicates the explanation or cause behind why one entity was incorrectly identified as another.
- F. None of above.
Provenance (3 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_69f76daeb6e48190a4c9a6b0edc80f72 |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77ffa6b68819090257fed3802c239 |
completed | May 3, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69f7795978c481909e152cd1bd02dd07 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 3, 2026, 3:59 p.m.