Triple
T11776951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portrait of Virginia Woolf |
E280041
|
entity |
| Predicate | artistSiblingOfDepicted |
P101531
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Portrait of Virginia Woolf, artistSiblingOfDepicted, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: artistSiblingOfDepicted Context triple: [Portrait of Virginia Woolf, artistSiblingOfDepicted, true]
-
A.
sibling
Indicates that two entities share at least one parent, making them brothers or sisters to each other.
-
B.
isEldestSisterOf
Indicates that one person is the oldest female sibling in relation to another person.
-
C.
portrayedFamilyMemberOf
Indicates that one entity has depicted another entity as a member of their family, typically in a creative or representational context such as art, film, or literature.
-
D.
adoptiveSister
Indicates a sisterly relationship where one person is the sister of another through legal adoption rather than biological parentage.
-
E.
isFictionalTwinOf
Indicates that one entity is the imagined or fictional twin counterpart of another entity, typically within a narrative or creative context.
- F. None of above. chosen
Provenance (4 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_69d6ab01d2688190ad8ed6bda487eaa5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a8c2e8b08190a31b1e284fca2aee |
completed | April 10, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69d8a242cd8c819086ed6c5f292dc8cb |
completed | April 10, 2026, 7:09 a.m. |
| PDg | Predicate description generation | batch_69d8a8c07d648190b8650d31f3a15090 |
completed | April 10, 2026, 7:37 a.m. |
Created at: April 8, 2026, 9:42 p.m.