Triple
T943253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dionysia |
E20352
|
entity |
| Predicate | sponsorRole |
P2590
|
FINISHED |
| Object | choregos |
—
|
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: choregos | Statement: [Dionysia, sponsorRole, choregos]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sponsorRole Context triple: [Dionysia, sponsorRole, choregos]
-
A.
sponsorType
chosen
Indicates the specific role or category of sponsorship that an entity provides in relation to another entity or event.
-
B.
sponsorLevel
Indicates the degree or tier of sponsorship that one entity provides to another.
-
C.
supportsRole
Indicates that one entity provides the necessary functionality, resources, or conditions for another entity to perform or occupy a specific role.
-
D.
sponsorInHouse
Indicates that one entity formally supports, promotes, or funds another entity within the same organization, institution, or internal setting.
-
E.
promotionalRole
Indicates that an entity serves in a capacity focused on promoting, advertising, or publicizing another entity, product, or 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_69a493b0270c81909e6c9ce310f6aa55 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3a2b1ec8190a2753ad3b3e8cc7a |
completed | March 1, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69a4b29dc8dc8190b9d33f70f8563d61 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.