Triple
T12288069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Life of an American Fireman |
E292880
|
entity |
| Predicate | intertitles |
P7742
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Life of an American Fireman, intertitles, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intertitles Context triple: [Life of an American Fireman, intertitles, English]
-
A.
containsIntertitlesFrom
Indicates that one entity includes or incorporates intertitles that originate from another entity.
-
B.
silentWithIntertitles
Indicates that a work is a silent production that conveys dialogue or narrative information through intertitles rather than synchronized spoken sound.
-
C.
hasIntertitlesLanguage
chosen
Indicates that the intertitles of a film or audiovisual work are presented in a specified language.
-
D.
titles
Indicates that one entity holds a formal title, designation, or name associated with another entity.
-
E.
internationalTitle
Indicates that an entity has a title or name used in international or cross-border contexts, distinct from its local or original title.
- 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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9261e1570819084bb4fdb44aa6aea |
completed | April 10, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69d91c4d9a9c8190aeb7beaf9792d8f0 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.