Triple
T12107566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North by Northwest (1959 film) score |
E288340
|
entity |
| Predicate | hasMainTitleCue |
P103324
|
FINISHED |
| Object | Main Title from North by Northwest |
—
|
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: Main Title from North by Northwest | Statement: [North by Northwest (1959 film) score, hasMainTitleCue, Main Title from North by Northwest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainTitleCue Context triple: [North by Northwest (1959 film) score, hasMainTitleCue, Main Title from North by Northwest]
-
A.
hasPrimaryTitle
Indicates that an entity is associated with its main or official title, distinguishing it from any alternative or secondary titles.
-
B.
hasMainTitleCharacter
Indicates that a work’s primary or main title is centered on, derived from, or explicitly names a particular character.
-
C.
hasMajorTitle
Indicates that an entity holds or has been awarded a significant, high-prestige title or championship.
-
D.
hasTitleIn
Indicates that an entity holds or is associated with a specific title within a particular context, domain, or language.
-
E.
hasTitleSubject
Indicates that an entity has a specific subject or topic as the focus of its title.
- 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_69d6ab4a5c448190a110d1273314b21a |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9164ada5081908676bd9e5947268a |
completed | April 10, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69d9150497408190921334d21503375a |
completed | April 10, 2026, 3:19 p.m. |
| PDg | Predicate description generation | batch_69d916481a008190ae66677b9e6dd961 |
completed | April 10, 2026, 3:24 p.m. |
Created at: April 8, 2026, 9:49 p.m.