Triple
T14657066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Mom |
E344137
|
entity |
| Predicate | screenwriterNationality |
P115234
|
FINISHED |
| Object | American |
—
|
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: American | Statement: [Mr. Mom, screenwriterNationality, American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: screenwriterNationality Context triple: [Mr. Mom, screenwriterNationality, American]
-
A.
screenwriterCreator
Indicates that one entity is the screenwriter who created or authored the screenplay for another entity (such as a film, episode, or audiovisual work).
-
B.
screenwriterCreatedBy
Indicates that a screenwriter was created, conceived, or brought into existence by a particular entity (such as a person, organization, or work).
-
C.
screenwriterOfWorkCreator
Indicates that one entity is the screenwriter who created or wrote the screenplay for a particular work.
-
D.
screenwriterOfDepiction
Indicates that one entity is the screenwriter responsible for the script of a particular depiction or representation of a work or subject.
-
E.
screenwriterCreditContext
Indicates the contextual details or circumstances under which a person is credited as a screenwriter for a particular work.
- 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_69d822e1a2cc81908e5bb93cf61ce3cc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb51a562c819098971447db4b29f7 |
completed | April 14, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69de6576f0208190aa94d995e797ac38 |
completed | April 14, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69de716c17cc8190aeb85296abee85a7 |
completed | April 14, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:27 a.m.