Triple
T35142750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alice Knight Buffay |
E1014738
|
entity |
| Predicate | fictionalSpouseOf |
P138299
|
FINISHED |
| Object | Frank Buffay Jr. |
—
|
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: Frank Buffay Jr. | Statement: [Alice Knight Buffay, fictionalSpouseOf, Frank Buffay Jr.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalSpouseOf Context triple: [Alice Knight Buffay, fictionalSpouseOf, Frank Buffay Jr.]
-
A.
spouseCharacterOf
chosen
Indicates a marital relationship where one character is the spouse of another character.
-
B.
spouseOfProtagonistOf
Indicates that one entity is the spouse (married partner) of the main character (protagonist) of another entity, typically a narrative work.
-
C.
spouseCharacterPlayed
Indicates that one entity is the spouse of the character portrayed by another entity.
-
D.
allegedSpouseOf
Indicates a relationship where one person is claimed or reported to be the spouse of another, but the marital status is not legally or definitively confirmed.
-
E.
sometimesSpouseOf
Indicates that two entities are occasionally, but not consistently or permanently, in a spousal relationship with each other.
- 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_69f76dda7c108190a2ffd93eb6c341a7 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fef112398081909237c3872345968b |
completed | May 9, 2026, 8:32 a.m. |
| PD | Predicate disambiguation | batch_69feefb14ec08190ab401987d8c84a23 |
completed | May 9, 2026, 8:26 a.m. |
Created at: May 3, 2026, 4:02 p.m.