Triple
T17724597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Continence of Scipio |
E442427
|
entity |
| Predicate | portraysSetting |
P54861
|
FINISHED |
| Object | Roman military camp |
—
|
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: Roman military camp | Statement: [The Continence of Scipio, portraysSetting, Roman military camp]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysSetting Context triple: [The Continence of Scipio, portraysSetting, Roman military camp]
-
A.
portrayedInSetting
chosen
Indicates that an entity is depicted or represented within a particular setting, environment, or context.
-
B.
portrayalFeature
Indicates that one entity serves as a characteristic, aspect, or attribute highlighted in the depiction or representation of another entity.
-
C.
portraysState
Indicates that one entity visually or symbolically represents or depicts the condition, status, or situation of another entity.
-
D.
portraysDevice
Indicates that one entity visually represents or depicts a device in some medium or context.
-
E.
portraysActivity
Indicates that one entity visually or narratively represents another entity engaged in a particular activity.
- 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4748900608190bf5ba04415edaffc |
completed | April 19, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69e3cde815e08190881972e2d80d151e |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:07 a.m.