Triple
T27240204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Light of Asia |
E687184
|
entity |
| Predicate | hasOriginalIntertitlesLanguage |
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: [The Light of Asia, hasOriginalIntertitlesLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginalIntertitlesLanguage Context triple: [The Light of Asia, hasOriginalIntertitlesLanguage, English]
-
A.
hasIntertitlesLanguage
chosen
Indicates that the intertitles of a film or audiovisual work are presented in a specified language.
-
B.
hasOriginalTitleScript
Indicates that an entity’s original title is written or represented in a specific writing system or script.
-
C.
containsIntertitlesFrom
Indicates that one entity includes or incorporates intertitles that originate from another entity.
-
D.
originalTitleLanguage
Indicates the language in which a work’s original title was written or expressed.
-
E.
hasOriginalCountryTitle
Indicates that an entity is associated with the title it originally had in its country of origin.
- 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_69ef355547408190b5ca0d777c65040a |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f727afd5d88190ad48735cd1b32787 |
completed | May 3, 2026, 10:47 a.m. |
| PD | Predicate disambiguation | batch_69f72737c42c8190a3f781a5e98868ff |
completed | May 3, 2026, 10:45 a.m. |
Created at: April 27, 2026, 10:37 a.m.