Triple
T34619154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patsy Ruth Kahle |
E888949
|
entity |
| Predicate | spouseNotableWorkGenre |
P196097
|
FINISHED |
| Object | Western films |
—
|
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: Western films | Statement: [Patsy Ruth Kahle, spouseNotableWorkGenre, Western films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseNotableWorkGenre Context triple: [Patsy Ruth Kahle, spouseNotableWorkGenre, Western films]
-
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.
spouseNotableWorkLanguage
Indicates that the notable work of a person's spouse is expressed or created in a particular language.
-
D.
spouseNotableFor
Indicates that a person's spouse is recognized or distinguished for a particular achievement, role, or characteristic.
-
E.
spouseNotableAward
Indicates that a person’s spouse has received a notable award or honor.
- 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_69f349d584e08190b40b9f6281ad50c4 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fe066d62b48190867df334039be786 |
completed | May 8, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69fe03afde3c8190a5b9b0778d19eb1a |
completed | May 8, 2026, 3:39 p.m. |
| PDg | Predicate description generation | batch_69fe066b623c819085205fbea901e3cf |
completed | May 8, 2026, 3:51 p.m. |
Created at: May 1, 2026, 2:03 a.m.