Triple
T34321072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spa Resort Hawaiians |
E880735
|
entity |
| Predicate | hasNumberOfVisitorsPerYear |
P12597
|
FINISHED |
| Object | over 1 million |
—
|
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: over 1 million | Statement: [Spa Resort Hawaiians, hasNumberOfVisitorsPerYear, over 1 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfVisitorsPerYear Context triple: [Spa Resort Hawaiians, hasNumberOfVisitorsPerYear, over 1 million]
-
A.
typicalVisitorsPerSeason
Indicates the usual number of visitors associated with each season for a given entity or location.
-
B.
touristArrivalsPerYearApprox
chosen
Indicates an approximate count of how many tourists arrive at a place over the course of a year.
-
C.
hasNumberOfOccurrencesPerYear
Indicates the relationship that specifies how many times something happens within a one-year period.
-
D.
hasVisitorsFrom
Indicates that an entity receives or has received visitors originating from another specified entity or location.
-
E.
visitYear
Indicates the specific year in which a visit or visitation event took place.
- 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_69f349b9cd508190a996a616903b3e6d |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fe9fb9735c8190a360b556c9d00b3f |
completed | May 9, 2026, 2:45 a.m. |
| PD | Predicate disambiguation | batch_69fe9eaa88008190a9b2a469dc685002 |
completed | May 9, 2026, 2:40 a.m. |
Created at: May 1, 2026, 1:57 a.m.