Triple
T2633149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lubin Manufacturing Company |
E59680
|
entity |
| Predicate | languageOfIntertitles |
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: [Lubin Manufacturing Company, languageOfIntertitles, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfIntertitles Context triple: [Lubin Manufacturing Company, languageOfIntertitles, English]
-
A.
hasIntertitlesLanguage
chosen
Indicates that the intertitles of a film or audiovisual work are presented in a specified language.
-
B.
languageOfAlternativeTitle
Indicates the language in which an alternative or variant title of an entity is expressed.
-
C.
originalTitleLanguage
Indicates the language in which a work’s original title was written or expressed.
-
D.
silentWithIntertitles
Indicates that a work is a silent production that conveys dialogue or narrative information through intertitles rather than synchronized spoken sound.
-
E.
originalLanguageTitle
Indicates the title of a work as it appears in its original language of creation or publication.
- 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_69ab4ac8596c8190b34997e73d9e991c |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abdb0e7b888190bfa5d2e33f00ec0f |
completed | March 7, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69abd810d7f481908e81c305772c4c14 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.