Triple
T20684106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Centennial Exposition |
E508368
|
entity |
| Predicate | visitorCountApproximate |
P427
|
FINISHED |
| Object | about 10 million 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: about 10 million visitors | Statement: [Centennial Exposition, visitorCountApproximate, about 10 million visitors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visitorCountApproximate Context triple: [Centennial Exposition, visitorCountApproximate, about 10 million visitors]
-
A.
visitorCount
chosen
Indicates the number of visitors associated with a particular entity, context, or time period.
-
B.
visitorFrequency
Indicates how often a visitor comes to or interacts with a particular entity or location.
-
C.
estimatedMemberCount
Indicates the approximate or predicted number of members associated with an entity.
-
D.
visitorScore
Indicates the number of points or goals scored by the visiting/away participant in a game or contest.
-
E.
guestCountApproximate
Indicates that the number of guests involved is represented as an estimated or approximate count rather than an exact figure.
- 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_69e0b4c1ed408190b72dd26b1e33f8a1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6beaae5608190ac8cc64aa4717d53 |
completed | April 21, 2026, 12:02 a.m. |
| PD | Predicate disambiguation | batch_69e5c03caee881908be4dd25796a03d5 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 11:45 a.m.