Triple
T38577094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delray Affair |
E929434
|
entity |
| Predicate | approximateNumberOfExhibitors |
P143910
|
FINISHED |
| Object | hundreds of exhibitors |
—
|
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: hundreds of exhibitors | Statement: [Delray Affair, approximateNumberOfExhibitors, hundreds of exhibitors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfExhibitors Context triple: [Delray Affair, approximateNumberOfExhibitors, hundreds of exhibitors]
-
A.
exhibitorsNumber
chosen
Indicates the total count of exhibitors associated with a given event or exhibition.
-
B.
hasExhibitors
Indicates that an entity includes, hosts, or is associated with one or more exhibitors.
-
C.
numberOfExhibits
Indicates the total count of exhibits associated with a given entity or context.
-
D.
exhibitorsFrom
Indicates a relationship where certain exhibitors originate from, are associated with, or come from a specified source, location, or organization.
-
E.
approximateNumberOfPerformers
Indicates an estimated count of performers involved in an event or performance.
- 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_69f76ebd2248819083978362d81fa35e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a00037bf4148190a58593d30efdd3f8 |
completed | May 10, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_6a0000b7af608190b718fc4111bcdad8 |
completed | May 10, 2026, 3:51 a.m. |
Created at: May 3, 2026, 4:32 p.m.