Triple
T35261127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bread and Circuses |
E1018371
|
entity |
| Predicate | portraysEntertainmentForm |
P110358
|
FINISHED |
| Object | arena combat as mass entertainment |
—
|
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: arena combat as mass entertainment | Statement: [Bread and Circuses, portraysEntertainmentForm, arena combat as mass entertainment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysEntertainmentForm Context triple: [Bread and Circuses, portraysEntertainmentForm, arena combat as mass entertainment]
-
A.
entertainmentType
Indicates the kind or category of entertainment associated with an entity or event.
-
B.
portraysActivity
chosen
Indicates that one entity visually or narratively represents another entity engaged in a particular activity.
-
C.
portraysArtForm
Indicates that one entity artistically represents, depicts, or expresses a particular art form.
-
D.
portrayalFormat
Indicates the medium or format in which something is portrayed or represented (e.g., painting, sculpture, film, digital).
-
E.
filmPortrayer
Indicates that one entity portrays or plays the role of another entity (such as a character or person) in a film.
- 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_69f76de4be5c8190a51705c07612cac8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff3fb2318c81908a46c2f513608935 |
completed | May 9, 2026, 2:07 p.m. |
| PD | Predicate disambiguation | batch_69ff3e96dcc48190819f6204680d84aa |
completed | May 9, 2026, 2:03 p.m. |
Created at: May 3, 2026, 4:02 p.m.