Triple
T32087983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman sestertius |
E819500
|
entity |
| Predicate | reverseUsuallyDepicts |
P94330
|
FINISHED |
| Object | allegorical 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: allegorical figures | Statement: [Roman sestertius, reverseUsuallyDepicts, allegorical figures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reverseUsuallyDepicts Context triple: [Roman sestertius, reverseUsuallyDepicts, allegorical figures]
-
A.
reversed
Indicates that the direction or order of a previously defined relationship or sequence between entities is inverted.
-
B.
typicalReverseType
Indicates that the subject is the usual or canonical inverse relation type of the given predicate.
-
C.
reverseModeDescription
Indicates that the relationship specifies a textual explanation of how a process or system operates in its reverse or opposite mode.
-
D.
reverseFeature
Indicates that one feature is the inverse or opposite counterpart of another feature in a given context.
-
E.
typicallyDepicts
chosen
Indicates that one entity is most commonly or characteristically portrayed or represented by the other in depictions or images.
- 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_69f349004b2481908ce2e50af0d579a8 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b58d7e5081909718343bc2a900db |
completed | May 3, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a7bdb481908d16a32f49e38c2c |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:25 a.m.