Triple
T4811021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Queen of Spades |
E107067
|
entity |
| Predicate | differenceFromSource |
P57180
|
FINISHED |
| Object | expanded love story between Hermann and Liza |
—
|
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: expanded love story between Hermann and Liza | Statement: [The Queen of Spades, differenceFromSource, expanded love story between Hermann and Liza]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: differenceFromSource Context triple: [The Queen of Spades, differenceFromSource, expanded love story between Hermann and Liza]
-
A.
differenceFromStates
Indicates that one state or condition is distinct from, or deviates in some way from, another state or condition.
-
B.
differsFromSourceMaterial
chosen
Indicates that something has been altered or deviates in some way from its original or reference source material.
-
C.
differentiatedFrom
Indicates that one entity is distinguished or set apart from another by identifying differences between them.
-
D.
hasLexicalDifferencesWith
Indicates that two linguistic items differ from each other in their word choice or lexical form.
-
E.
differenceFromUDP
Indicates a relationship where something is characterized or measured in terms of how it differs from UDP (User Datagram Protocol) in behavior, properties, or implementation.
- 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_69bd43f779448190b92885cb70abb6c2 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ff981fc819080d4466c6fe06cf3 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1c43a48190a65e56b1624a2339 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:23 p.m.