Triple
T29642661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vera Budnick |
E755903
|
entity |
| Predicate | spouseNotableWorkPeriod |
P186966
|
FINISHED |
| Object | mid-20th century 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: mid-20th century cinema | Statement: [Vera Budnick, spouseNotableWorkPeriod, mid-20th century cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseNotableWorkPeriod Context triple: [Vera Budnick, spouseNotableWorkPeriod, mid-20th century cinema]
-
A.
spouseNotableWorkField
Indicates that the notable work or professional field associated with a person’s spouse is being specified.
-
B.
spouse notableWork
Indicates that a person's spouse is significantly associated with a particular notable work.
-
C.
spouseNotableFor
Indicates that a person's spouse is recognized or distinguished for a particular achievement, role, or characteristic.
-
D.
spouseNotableWorkLanguage
Indicates that the notable work of a person's spouse is expressed or created in a particular language.
-
E.
spouseEra
Indicates that two individuals are spouses during a specified historical period or era.
- F. None of above. chosen
Provenance (4 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_69f0ef89d2c88190a6d0d5116ccd7cc9 |
completed | April 28, 2026, 5:34 p.m. |
| NER | Named-entity recognition | batch_69fb2e940d5c8190bceae77daf4ef512 |
completed | May 6, 2026, 12:05 p.m. |
| PD | Predicate disambiguation | batch_69f9fec70bd881909c658a3c5020318b |
completed | May 5, 2026, 2:29 p.m. |
| PDg | Predicate description generation | batch_69fb2e9309fc81909dfefd9020d6fbad |
completed | May 6, 2026, 12:05 p.m. |
Created at: April 28, 2026, 6:47 p.m.