Triple
T221036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tulip Time Festival |
E4212
|
entity |
| Predicate | draws |
P10119
|
FINISHED |
| Object | regional visitors |
—
|
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: regional visitors | Statement: [Tulip Time Festival, draws, regional visitors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: draws Context triple: [Tulip Time Festival, draws, regional visitors]
-
A.
drawsLesson
Indicates that one entity derives or infers a lesson or conclusion from another entity or situation.
-
B.
paintedEvery
Indicates that an entity applied paint to each and every relevant item in a specified set or domain.
-
C.
artworkType
Indicates the specific category or kind of artwork that characterizes the relationship between the subject and the artwork.
-
D.
depicts
Indicates that one entity visually represents, portrays, or shows another entity.
-
E.
artForm
Indicates the type or category of artistic expression that characterizes or defines something (e.g., painting, music, dance).
- 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_69a2573508588190b522c2476d91acfe |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25efd0df48190b8fef4c422a1265f |
completed | Feb. 28, 2026, 3:20 a.m. |
| PD | Predicate disambiguation | batch_69a25b54d790819093b35bd1a6f00f92 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25efc13308190900a86ca0367c9b3 |
completed | Feb. 28, 2026, 3:20 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.