Triple
T10212237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jubilee Year 2000 exposition |
E242356
|
entity |
| Predicate | approximateNumberOfAttendees |
P3846
|
FINISHED |
| Object | millions of pilgrims |
—
|
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: millions of pilgrims | Statement: [Jubilee Year 2000 exposition, approximateNumberOfAttendees, millions of pilgrims]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfAttendees Context triple: [Jubilee Year 2000 exposition, approximateNumberOfAttendees, millions of pilgrims]
-
A.
guestCountApproximate
Indicates that the number of guests involved is represented as an estimated or approximate count rather than an exact figure.
-
B.
approximateAudienceSize
chosen
Indicates an estimated number of individuals or entities that are expected to be reached or affected in a given context.
-
C.
estimatedCumulativeAttendance
Indicates the total number of attendees expected to have been present over a period of time, aggregated up to a given point.
-
D.
estimatedMemberCount
Indicates the approximate or predicted number of members associated with an entity.
-
E.
audienceSizeApproximate
Indicates an estimated or approximate number of people in the audience for an event or content.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa23bce881909b5deac612ec22cb |
completed | April 6, 2026, 12:42 p.m. |
| PD | Predicate disambiguation | batch_69d39559e5ac8190b88eca75956b7e6a |
completed | April 6, 2026, 11:13 a.m. |
Created at: April 6, 2026, 11:02 a.m.