Triple
T1663818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iberian sculpture |
E35966
|
entity |
| Predicate | commonMotif |
P2366
|
FINISHED |
| Object | seated female figures |
—
|
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: seated female figures | Statement: [Iberian sculpture, commonMotif, seated female figures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonMotif Context triple: [Iberian sculpture, commonMotif, seated female figures]
-
A.
primaryMotif
chosen
Indicates that one entity serves as the main recurring theme or dominant motif associated with another entity.
-
B.
reverseMotif
Indicates that one motif is the reversed or inverted form of another motif in structure, order, or direction.
-
C.
notableMutualism
Indicates a significant mutually beneficial relationship between two entities, where each provides important advantages or services to the other.
-
D.
abductionMotif
Indicates a relationship where an event, narrative, or depiction involves the motif of one entity abducting or forcibly carrying off another.
-
E.
relatedMIC
Indicates that there exists a relationship or connection between entities involving a MIC (Minimum Inhibitory Concentration) context, such as shared, comparable, or associated MIC values or measurements.
- 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_69a88606aa808190aa0b421b4271f220 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa994f92b0819084ee2f6a672334b9 |
completed | March 6, 2026, 9:07 a.m. |
| PD | Predicate disambiguation | batch_69a907d2475c8190b7ec7dccd3335eb1 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:29 p.m.