Triple
T11995175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert De Niro as Dr. Wally |
E285509
|
entity |
| Predicate | associatedWorkIMDbId |
P7954
|
FINISHED |
| Object | tt0116999 |
—
|
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: tt0116999 | Statement: [Robert De Niro as Dr. Wally, associatedWorkIMDbId, tt0116999]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWorkIMDbId Context triple: [Robert De Niro as Dr. Wally, associatedWorkIMDbId, tt0116999]
-
A.
filmAssociatedWith
Indicates a general relationship or connection between a film and another entity, such as a person, organization, event, or work.
-
B.
associatedWorkSubtitle
Indicates the subtitle of a related or associated work.
-
C.
hasIMDbId
chosen
Indicates that an entity is associated with a specific identifier used by the Internet Movie Database (IMDb) to uniquely reference it.
-
D.
associatedWork
Indicates that there exists a related or connected work (such as a publication, creative piece, or project) that is meaningfully linked to the subject.
-
E.
linkedFilm
Indicates that there is an associated or connected film related to the given entity.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903b211688190bfe6dd15c3f96d2f |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d902abca70819098291aa51b593708 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.