Triple
T5188815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | J. Alfred Prufrock |
E117097
|
entity |
| Predicate | ageDepiction |
P13483
|
FINISHED |
| Object | middle-aged |
—
|
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: middle-aged | Statement: [J. Alfred Prufrock, ageDepiction, middle-aged]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageDepiction Context triple: [J. Alfred Prufrock, ageDepiction, middle-aged]
-
A.
portraysAgeGroup
chosen
Indicates that one entity depicts or represents another entity as belonging to a particular age group.
-
B.
oftenDepictedAs
Indicates that one entity is frequently represented or portrayed in the form, appearance, or symbolism of another entity.
-
C.
depictsSex
Indicates that one entity visually represents or portrays sexual activity or sexual content involving another entity.
-
D.
depictionType
Indicates the specific manner or style in which something is visually represented or depicted.
-
E.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of 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_69bd44620ff48190bcac01782107a397 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd79c732b48190af62dfffcbc5e3a6 |
completed | March 20, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69bd77b7e8b4819092ec3965e11f2dea |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:46 p.m.