Triple
T7809490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hot Water |
E180640
|
entity |
| Predicate | hasSilentFilmIntertitlesLanguage |
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: [Hot Water, hasSilentFilmIntertitlesLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSilentFilmIntertitlesLanguage Context triple: [Hot Water, hasSilentFilmIntertitlesLanguage, 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.
containsIntertitlesFrom
Indicates that one entity includes or incorporates intertitles that originate from another entity.
-
D.
hasSubtitles
Indicates that one media item provides subtitle text or tracks that accompany another media item or its audio content.
-
E.
languageOfSubtitles
Indicates the language in which the subtitles for a given media item are provided.
- 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_69ca827f6f148190beca4e245b993506 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78bb4b08190b2b3b51c5a0a033c |
completed | March 30, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69cae91687788190af9cb7aaa996d291 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:36 p.m.