Triple
T24076771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jane Arden |
E596384
|
entity |
| Predicate | spouseOfNotableWorkDomain |
P22220
|
FINISHED |
| Object | classic Hollywood cinema |
—
|
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: classic Hollywood cinema | Statement: [Jane Arden, spouseOfNotableWorkDomain, classic Hollywood cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseOfNotableWorkDomain Context triple: [Jane Arden, spouseOfNotableWorkDomain, classic Hollywood cinema]
-
A.
spouseNotableWorkField
chosen
Indicates that the notable work or professional field associated with a person’s spouse is being specified.
-
B.
spouseNotableFor
Indicates that a person's spouse is recognized or distinguished for a particular achievement, role, or characteristic.
-
C.
spouseNotableWorkLanguage
Indicates that the notable work of a person's spouse is expressed or created in a particular language.
-
D.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
E.
spouseOfWork
Indicates that one person is the spouse of another specifically in the context of their workplace or professional environment.
- 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_69e288c3999c8190809b282a04813dec |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1db1e959c81909f4365b5d7f934d9 |
completed | April 29, 2026, 10:19 a.m. |
| PD | Predicate disambiguation | batch_69f1764b1d4c8190b12590c6339c31c1 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 10:42 p.m.