Triple
T10313953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bellagio (Las Vegas) |
E241965
|
entity |
| Predicate | fountainShowFrequency |
P16914
|
FINISHED |
| Object | every 15 to 30 minutes depending on time of day |
—
|
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: every 15 to 30 minutes depending on time of day | Statement: [Bellagio (Las Vegas), fountainShowFrequency, every 15 to 30 minutes depending on time of day]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fountainShowFrequency Context triple: [Bellagio (Las Vegas), fountainShowFrequency, every 15 to 30 minutes depending on time of day]
-
A.
numberOfFountains
Indicates the quantitative relationship specifying how many fountains are associated with a given entity.
-
B.
carnivalFrequency
Indicates how often a carnival event occurs within a given time period.
-
C.
exhibitionFrequency
Indicates how often an entity is displayed, presented, or exhibited within a given context or time period.
-
D.
performedFrequency
chosen
Indicates how often an action or activity is carried out within a given time period.
-
E.
hasFestivalFrequency
Indicates how often a festival or recurring celebratory event takes place within a given time period.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f4f354819080b4ed4bc61bdff6 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:48 a.m.