Triple
T15188791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portrait of the Family of Herman Boerhaave |
E362947
|
entity |
| Predicate | depictsGenderMix |
P109486
|
FINISHED |
| Object | men, women and children |
—
|
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: men, women and children | Statement: [Portrait of the Family of Herman Boerhaave, depictsGenderMix, men, women and children]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsGenderMix Context triple: [Portrait of the Family of Herman Boerhaave, depictsGenderMix, men, women and children]
-
A.
genderDepicted
Indicates that the relationship specifies the gender of the entity as it is represented or portrayed in some context.
-
B.
hasGenderRepresentation
chosen
Indicates that something includes, reflects, or portrays one or more genders within its content, structure, or composition.
-
C.
genderOfMembers
Indicates the gender or genders associated with the members of a group or organization.
-
D.
genderOfResidents
Indicates the gender identity or classification associated with the residents of a particular place or group.
-
E.
includesMixedSexRace
Indicates that the group or context involves individuals of more than one sex and more than one race.
- 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_69d85a09a39c81908759f23268e2d408 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0067beedc8190abc0a94c7a38f85e |
completed | April 15, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69deb97bd8bc8190b2ad4888f97cf963 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:09 a.m.