Triple
T37822250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Among Those Present |
E942949
|
entity |
| Predicate | hasSilentIntertitlesLanguage |
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: [Among Those Present, hasSilentIntertitlesLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSilentIntertitlesLanguage Context triple: [Among Those Present, hasSilentIntertitlesLanguage, English]
-
A.
hasIntertitlesLanguage
chosen
Indicates that the intertitles of a film or audiovisual work are presented in a specified language.
-
B.
silentWithIntertitles
Indicates that a work is a silent production that conveys dialogue or narrative information through intertitles rather than synchronized spoken sound.
-
C.
hasNoIntertitles
Indicates that the work (typically a film or video) does not contain any intertitles or title cards within its content.
-
D.
containsIntertitlesFrom
Indicates that one entity includes or incorporates intertitles that originate from another entity.
-
E.
usesIntertitlesInSegment
Indicates that intertitles are employed within a specific segment of a work (such as a film or video) to convey information or dialogue.
- 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_69f76ee987588190906506e759be5db3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fe7b1c506c8190869c1a22031e0571 |
completed | May 9, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69fe796b2bdc8190a86980d44008f875 |
completed | May 9, 2026, 12:01 a.m. |
Created at: May 3, 2026, 4:19 p.m.