Triple
T31405329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Jane Grant |
E801110
|
entity |
| Predicate | spouseOfFictionalRole |
P106611
|
FINISHED |
| Object | John Shaft |
—
|
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: John Shaft | Statement: [Mary Jane Grant, spouseOfFictionalRole, John Shaft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseOfFictionalRole Context triple: [Mary Jane Grant, spouseOfFictionalRole, John Shaft]
-
A.
spouseCharacterOf
Indicates a marital relationship where one character is the spouse of another character.
-
B.
spouseCharacterPlayed
Indicates that one entity is the spouse of the character portrayed by another entity.
-
C.
spouseOfRole
chosen
Indicates that one role is the spouse (husband, wife, or equivalent marital partner) of another role.
-
D.
spouseOfProtagonistOf
Indicates that one entity is the spouse (married partner) of the main character (protagonist) of another entity, typically a narrative work.
-
E.
spouseOccupationInFiction
Indicates that a person’s spouse has a particular occupation within a fictional work or narrative context.
- 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_69f348c0dd648190bf2fd7642f78eb06 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fd485f57dc8190820365396d041991 |
completed | May 8, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69fd47d35da081908bec8901018d186c |
completed | May 8, 2026, 2:17 a.m. |
Created at: April 30, 2026, 8:31 p.m.