Triple
T27931656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portrait of a Young Girl (Cornelis de Vos) |
E707996
|
entity |
| Predicate | subjectAgeCategory |
P125218
|
FINISHED |
| Object | child |
—
|
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: child | Statement: [Portrait of a Young Girl (Cornelis de Vos), subjectAgeCategory, child]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectAgeCategory Context triple: [Portrait of a Young Girl (Cornelis de Vos), subjectAgeCategory, child]
-
A.
ageCategoryDefinition
Indicates the rule or criteria that define how ages are grouped into specific age categories.
-
B.
ageType
Indicates the specific categorization or classification of an age value (e.g., actual, estimated, range-based) associated with an entity.
-
C.
subjectAgeAtEvent
Indicates the age of a subject at the time a specific event occurs.
-
D.
ageGroupIndicated
chosen
Indicates that a specific age range or category is identified or assigned to an entity.
-
E.
ageStatus
Indicates the relationship between an entity and its classification into an age-related category or status (e.g., minor, adult, senior).
- 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_69ef96bbf2c48190a9d0e0291457aab6 |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f6b903538481909cffcb6cc1cc0e70 |
completed | May 3, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69f6b626120c819097c9ad04487570d7 |
completed | May 3, 2026, 2:42 a.m. |
Created at: April 27, 2026, 7:03 p.m.