Triple
T22068045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sophia Afendaki (Sleeping Girl sculpture) |
E545329
|
entity |
| Predicate | hasSubjectCondition |
P1255
|
FINISHED |
| Object | eternal rest |
—
|
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: eternal rest | Statement: [Sophia Afendaki (Sleeping Girl sculpture), hasSubjectCondition, eternal rest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubjectCondition Context triple: [Sophia Afendaki (Sleeping Girl sculpture), hasSubjectCondition, eternal rest]
-
A.
hasCondition
chosen
Indicates that an entity possesses, experiences, or is affected by a particular condition or state.
-
B.
containsCondition
Indicates that one entity includes, embodies, or is associated with a particular condition.
-
C.
hasSubjectCount
Indicates that an entity is associated with a specific number of subjects.
-
D.
hasNumberOfConditions
Indicates that an entity is associated with a specific count of conditions it has or is subject to.
-
E.
hasSubjectEntriesIn
Indicates that a subject is recorded or represented within specific entries of a collection, dataset, or catalog.
- 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_69e11e344dfc81909b1d88a7221329c7 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12885fe04819092cdde142f91e147 |
completed | April 28, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69e6f64a6a70819089d1a6c3a2384861 |
completed | April 21, 2026, 4 a.m. |
Created at: April 16, 2026, 8:27 p.m.