Triple
T29958124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TomorrowWorld |
E760964
|
entity |
| Predicate | approximateAttendancePerYear |
P111137
|
FINISHED |
| Object | over 100,000 attendees |
—
|
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 100,000 attendees | Statement: [TomorrowWorld, approximateAttendancePerYear, over 100,000 attendees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateAttendancePerYear Context triple: [TomorrowWorld, approximateAttendancePerYear, over 100,000 attendees]
-
A.
estimatedCumulativeAttendance
Indicates the total number of attendees expected to have been present over a period of time, aggregated up to a given point.
-
B.
averageAttendancePerGame
Indicates the typical number of attendees present at each individual game over a given period.
-
C.
averageAttendanceTrend
Indicates how the average attendance changes over time, such as increasing, decreasing, or remaining stable.
-
D.
approximateAudienceSize
Indicates an estimated number of individuals or entities that are expected to be reached or affected in a given context.
-
E.
hasApproximateNumberOfPeople
chosen
Indicates that an entity is associated with an estimated or approximate count of people, rather than an exact number.
- 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_69f22466327481908ba6db916837bece |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fd91a5dad8819093eeeef527027890 |
completed | May 8, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69fd8f65fe9081908902500a3228d935 |
completed | May 8, 2026, 7:23 a.m. |
Created at: April 29, 2026, 6:28 p.m.