Triple
T5038998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Duchess of Alba by Francisco Goya |
E113498
|
entity |
| Predicate | depictsAgeOfSitter |
P13483
|
FINISHED |
| Object | adult |
—
|
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: adult | Statement: [The Duchess of Alba by Francisco Goya, depictsAgeOfSitter, adult]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsAgeOfSitter Context triple: [The Duchess of Alba by Francisco Goya, depictsAgeOfSitter, adult]
-
A.
sitterNationality
Indicates the national identity or citizenship of the person who is sitting for a portrait or being depicted.
-
B.
sitter
Indicates that one entity is serving as a caretaker or guardian, typically watching over or looking after another entity.
-
C.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
-
D.
portraysAgeGroup
chosen
Indicates that one entity depicts or represents another entity as belonging to a particular age group.
-
E.
caregiverOf
Indicates a relationship where one entity provides ongoing care, support, or supervision for another entity’s well-being.
- 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_69bd44384298819089c49e7c330ec7b8 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd73dbf00c819094b67809dafdecc6 |
completed | March 20, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_69bd71529d608190a53470ba6c14bb1d |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:37 p.m.