Triple
T32380830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enzian Theater |
E827410
|
entity |
| Predicate | isAnnualHostOf |
P174000
|
FINISHED |
| Object | Florida Film Festival |
—
|
NE NERFINISHED |
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: Florida Film Festival | Statement: [Enzian Theater, isAnnualHostOf, Florida Film Festival]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isAnnualHostOf Context triple: [Enzian Theater, isAnnualHostOf, Florida Film Festival]
-
A.
coHostOf
Indicates a relationship where two or more entities jointly host the same event, program, or activity together.
-
B.
wasGuestHostOf
Indicates that one entity temporarily served as a guest host for another entity’s show, program, or event.
-
C.
formerCoHostOf
Indicates that one entity previously served as a co-host together with another entity, but no longer holds that co-hosting role.
-
D.
notableYearForHost
Indicates the specific year in which a particular host is notably associated with an event, role, or activity.
-
E.
podcastHostOf
Indicates that one entity serves as the host of a particular podcast.
- 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_69f349177ddc8190ab0583f05597056b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c1bb5f248190834161b5a6ba1ece |
completed | May 3, 2026, 3:32 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6eb32c8190bf405b2011fa48f7 |
completed | May 3, 2026, 3:01 a.m. |
| PDg | Predicate description generation | batch_69f6bb344bb48190a8089f29c0063ded |
completed | May 3, 2026, 3:04 a.m. |
Created at: May 1, 2026, 12:51 a.m.