Triple
T37658698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | eDonkey2000 |
E937662
|
entity |
| Predicate | concurrentUsersAtPeak |
P92341
|
FINISHED |
| Object | millions of users |
—
|
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 users | Statement: [eDonkey2000, concurrentUsersAtPeak, millions of users]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: concurrentUsersAtPeak Context triple: [eDonkey2000, concurrentUsersAtPeak, millions of users]
-
A.
deploymentPeakNumber
Indicates the maximum number of deployments (or deployment instances) reached during a specified period or under given conditions.
-
B.
approximateUserPeak
chosen
Indicates that one value or event is an estimated or inferred maximum point associated with a particular user.
-
C.
hasNumberOfSeatsAtPeak
Indicates the maximum number of seats available or occupied at the peak usage or capacity of something.
-
D.
numberOfEmployeesAtPeak
Indicates the highest recorded count of employees that an entity had at any point in time.
-
E.
memberCountAtPeak
Indicates the highest number of members that an entity (such as a group or organization) has had at any point in time.
- 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_69f76ed6df7c8190b018e5baea716ceb |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaa1321b48190af92a3e7ec24ec5b |
completed | May 6, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69fba8860f98819080b7bab05837b974 |
completed | May 6, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:18 p.m.