Triple
T35914227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sieve Portrait |
E1038700
|
entity |
| Predicate | portraysAttribute |
P150464
|
FINISHED |
| Object | female chastity |
—
|
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: female chastity | Statement: [Sieve Portrait, portraysAttribute, female chastity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysAttribute Context triple: [Sieve Portrait, portraysAttribute, female chastity]
-
A.
depictsAttribute
Indicates that one entity visually represents or illustrates a specific attribute or characteristic of another entity.
-
B.
portrayalFeature
Indicates that one entity serves as a characteristic, aspect, or attribute highlighted in the depiction or representation of another entity.
-
C.
portraysRoleTrait
chosen
Indicates that one entity depicts or represents a particular role or character trait of another entity.
-
D.
conveysAttribute
Indicates that one entity communicates, expresses, or imparts a particular attribute or quality to another entity.
-
E.
portraysState
Indicates that one entity visually or symbolically represents or depicts the condition, status, or situation of another entity.
- 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_69f76e2320748190b7f5c4750d0cd0d3 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff5f5ecc808190b2df364da108ff4c |
completed | May 9, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69ff5b84131c8190bf81d7fb53e934bc |
completed | May 9, 2026, 4:06 p.m. |
Created at: May 3, 2026, 4:07 p.m.