Triple
T256964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marie Mosquini |
E5455
|
entity |
| Predicate | spouseOfNotablePerson |
P13
|
FINISHED |
| Object | inventor Lee de Forest |
—
|
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: inventor Lee de Forest | Statement: [Marie Mosquini, spouseOfNotablePerson, inventor Lee de Forest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseOfNotablePerson Context triple: [Marie Mosquini, spouseOfNotablePerson, inventor Lee de Forest]
-
A.
spouse
chosen
Indicates that two entities are married to each other in a legally or socially recognized partnership.
-
B.
spouseFamily
Indicates a family relationship formed through marriage, such as between a person and their spouse’s relatives.
-
C.
spouseOccupation
Indicates that one person’s spouse has a particular job, profession, or occupation.
-
D.
houseByMarriage
Indicates a familial or household relationship established through marriage rather than by blood or direct residence.
-
E.
notableCulturalFigure
Indicates that a person holds significant influence or recognition within a culture’s arts, traditions, values, or public life.
- 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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25d5884c88190a349d7593b688921 |
completed | Feb. 28, 2026, 3:13 a.m. |
| PD | Predicate disambiguation | batch_69a25b694c08819085bb4b256fa7736f |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.