Triple
T32294215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manny Garcia |
E825043
|
entity |
| Predicate | showOriginalLanguage |
P157397
|
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: [Manny Garcia, showOriginalLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: showOriginalLanguage Context triple: [Manny Garcia, showOriginalLanguage, English]
-
A.
originalLanguageText
Indicates that a text is expressed in its original, untranslated language.
-
B.
workInOriginalLanguage
chosen
Indicates that a work is being created, presented, or studied in the language in which it was originally produced, without translation.
-
C.
originalNameLanguage
Indicates that the specified language is the language in which an entity’s original or primary name was expressed.
-
D.
originalLanguageTitle
Indicates the title of a work as it appears in its original language of creation or publication.
-
E.
originalTitleLanguage
Indicates the language in which a work’s original title was written or expressed.
- 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_69f349101b788190b4f14884dc7d1ed2 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bd38959c8190ab96268f1c8016e7 |
completed | May 3, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69f6b632cf788190a3d0c08cd026b84b |
completed | May 3, 2026, 2:42 a.m. |
Created at: May 1, 2026, 12:44 a.m.