Triple
T37618294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tallie |
E935991
|
entity |
| Predicate | adaptedInScreenplayBy |
P181009
|
FINISHED |
| Object | Ron Hansen |
—
|
NE NERFINISHED |
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: Ron Hansen | Statement: [Tallie, adaptedInScreenplayBy, Ron Hansen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adaptedInScreenplayBy Context triple: [Tallie, adaptedInScreenplayBy, Ron Hansen]
-
A.
adaptedForFilmBy
Indicates that a work has been turned into a film by a particular person or entity responsible for the adaptation.
-
B.
screenwriterOfFilmAdaptation
chosen
Indicates that one entity is the screenwriter responsible for writing the screenplay of a film adaptation of another entity (typically a literary or original work).
-
C.
screenplayBy
Indicates that a film, television show, or similar work was written or scripted by a particular person or group.
-
D.
wroteScreenplaysFor
Indicates that one entity is the author or writer of screenplays created for another entity, such as a film, series, or production.
-
E.
screenwriterOfContainingFilm
Indicates that one entity is the screenwriter who wrote the screenplay for a film in which the other entity is contained (e.g., as a segment, episode, or part).
- 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_69f76ed16b748190ad6add183b1be688 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbacaf54648190811ea33b34907e8e |
completed | May 6, 2026, 9:03 p.m. |
| PD | Predicate disambiguation | batch_69fba883f770819091059c6f6c6af9f7 |
completed | May 6, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:18 p.m.