Triple
T19888925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dioxippus |
E477976
|
entity |
| Predicate | clothingDuringDuel |
P137713
|
FINISHED |
| Object | oiled naked body |
—
|
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: oiled naked body | Statement: [Dioxippus, clothingDuringDuel, oiled naked body]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clothingDuringDuel Context triple: [Dioxippus, clothingDuringDuel, oiled naked body]
-
A.
typeOfDuel
Indicates the specific kind or category of duel that characterizes a given dueling event or relationship between opponents.
-
B.
armour
Indicates that an entity provides protective covering or defense for another entity.
-
C.
wearsArmorOf
Indicates that one entity is equipped with or dressed in the specific armor that belongs to or is associated with another entity.
-
D.
armedBy
Indicates that one entity is supplied with weapons, equipment, or armaments by another entity.
-
E.
FrenchArmourUsed
Indicates that French-made armor was employed or utilized in a particular context or event.
- F. None of above. chosen
Provenance (4 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_69d8e51f32b08190b3687f4f60353250 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6590c1b9c8190abbfaa04b80713b3 |
completed | April 20, 2026, 4:49 p.m. |
| PD | Predicate disambiguation | batch_69e537ecda248190895c96afb6243823 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c136b081909cab9394b958390a |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:52 p.m.