Triple
T35943421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irene Dunne as Helen Lawrence |
E1039516
|
entity |
| Predicate | filmDistribution |
P184255
|
FINISHED |
| Object | Universal Pictures |
—
|
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: Universal Pictures | Statement: [Irene Dunne as Helen Lawrence, filmDistribution, Universal Pictures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmDistribution Context triple: [Irene Dunne as Helen Lawrence, filmDistribution, Universal Pictures]
-
A.
distributesFilmsFor
Indicates that one entity handles the distribution of films on behalf of another entity.
-
B.
distributedFilm
Indicates that one entity served as the distributor responsible for releasing or circulating a particular film.
-
C.
distributedFilmType
Indicates that a film was distributed in a particular format or category of distribution.
-
D.
filmOrganization
Indicates a relationship where an organization is involved with a film, such as producing, distributing, or otherwise being officially associated with it.
-
E.
distributedFilmsFrom
Indicates that one entity served as the distributor for films originating from another entity or source.
- 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_69f76e24bbd0819096b837d35371639a |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7acaec1508190a38f2ac9cc5383e7 |
completed | May 3, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f7ab734d848190a84f9b8c3a952b75 |
completed | May 3, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69f7ac2210e481909279dade5328825c |
completed | May 3, 2026, 8:12 p.m. |
Created at: May 3, 2026, 4:07 p.m.