Triple
T5112399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Problems of Parenthood |
E115245
|
entity |
| Predicate | hasSubtitlesIn |
P47403
|
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: [The Problems of Parenthood, hasSubtitlesIn, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubtitlesIn Context triple: [The Problems of Parenthood, hasSubtitlesIn, English]
-
A.
hasSubtitles
Indicates that one media item provides subtitle text or tracks that accompany another media item or its audio content.
-
B.
languageOfSubtitles
chosen
Indicates the language in which the subtitles for a given media item are provided.
-
C.
hasIntertitlesLanguage
Indicates that the intertitles of a film or audiovisual work are presented in a specified language.
-
D.
hasEP
Indicates that an entity possesses, is associated with, or is characterized by a specific EP (e.g., an endpoint, event point, or designated EP resource) in the given context.
-
E.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
- 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_69bd4441d1648190a54a533895041987 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75ca57e881908242def2a032902e |
completed | March 20, 2026, 4:28 p.m. |
| PD | Predicate disambiguation | batch_69bd715fe3a8819087d3065adddba515 |
completed | March 20, 2026, 4:10 p.m. |
Created at: March 20, 2026, 1:41 p.m.