Triple
T33059163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portrait of John Stuart Mill |
E845923
|
entity |
| Predicate | depictsNativeLanguage |
P186946
|
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: [Portrait of John Stuart Mill, depictsNativeLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsNativeLanguage Context triple: [Portrait of John Stuart Mill, depictsNativeLanguage, English]
-
A.
hasLanguageDepiction
Indicates that one entity is depicted, represented, or expressed using the language or linguistic form of another entity.
-
B.
alsoDepictsLanguage
Indicates that an item, in addition to its primary subject, also portrays or represents a particular language.
-
C.
languageUsedInDepiction
chosen
Indicates that a particular language is used within a depiction, such as in its text, dialogue, or other linguistic content.
-
D.
depictsNationality
Indicates that one entity visually represents or portrays the nationality or national identity of another entity.
-
E.
languageOfSurroundingCulture
Indicates that one entity is the language predominantly used or characteristic of the surrounding culture associated with another entity.
- 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_69f3495333b8819095e9af56855b9061 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fcc4b700748190ae00b21d09c96695 |
completed | May 7, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fcb0f9d3d881908a049475182fb039 |
completed | May 7, 2026, 3:34 p.m. |
Created at: May 1, 2026, 1:25 a.m.