Triple
T24076772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jane Arden |
E596384
|
entity |
| Predicate | spouseOfIndustry |
P87126
|
FINISHED |
| Object | film industry |
—
|
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: film industry | Statement: [Jane Arden, spouseOfIndustry, film industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseOfIndustry Context triple: [Jane Arden, spouseOfIndustry, film industry]
-
A.
spouseIndustry
chosen
Indicates the industry or sector in which a person's spouse is employed or primarily involved.
-
B.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
C.
spouseOfType
Indicates that one entity is the spouse of another, specifying the type or role of that spousal relationship.
-
D.
spouseOfWork
Indicates that one person is the spouse of another specifically in the context of their workplace or professional environment.
-
E.
spouseCharacterOf
Indicates a marital relationship where one character is the spouse of another character.
- 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.