Triple
T11590076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Expo 86 |
E274856
|
entity |
| Predicate | approximateVisitorCount |
P427
|
FINISHED |
| Object | about 22 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 22 million visitors | Statement: [Expo 86, approximateVisitorCount, about 22 million visitors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateVisitorCount Context triple: [Expo 86, approximateVisitorCount, about 22 million visitors]
-
A.
estimatedMemberCount
Indicates the approximate or predicted number of members associated with an entity.
-
B.
visitorCount
chosen
Indicates the number of visitors associated with a particular entity, context, or time period.
-
C.
visitorFrequency
Indicates how often a visitor comes to or interacts with a particular entity or location.
-
D.
approximateAudienceSize
Indicates an estimated number of individuals or entities that are expected to be reached or affected in a given context.
-
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_69d6aae6b14c81908dc5a74bad7591f9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d894643ae48190837502b713f5b9c6 |
completed | April 10, 2026, 6:10 a.m. |
| PD | Predicate disambiguation | batch_69d85dcbacd0819094d4a1237055affa |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:38 p.m.