Triple
T13423905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chandos portrait of William Shakespeare |
E313427
|
entity |
| Predicate | depictsHumanAge |
P13483
|
FINISHED |
| Object | middle-aged man |
—
|
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 man | Statement: [Chandos portrait of William Shakespeare, depictsHumanAge, middle-aged man]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsHumanAge Context triple: [Chandos portrait of William Shakespeare, depictsHumanAge, middle-aged man]
-
A.
ageDepictionConsistency
Indicates that the depicted age of an entity is consistent with its known or expected age within the given context.
-
B.
depictsLifePeriod
Indicates that one entity visually represents or portrays a specific period or phase in the life of another entity.
-
C.
portraysAgeGroup
chosen
Indicates that one entity depicts or represents another entity as belonging to a particular age group.
-
D.
typicalAge
Indicates the usual or characteristic age associated with an entity, event, or condition.
-
E.
characterAgeDescriptor
Indicates how a character’s age is qualitatively described or categorized (e.g., young, middle-aged, elderly) rather than given as a specific number.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaecf13748190ae40c7b95164f914 |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a0355de48190bb3fb96912e20df3 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:39 p.m.