Triple
T10159077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Undernet |
E233841
|
entity |
| Predicate | hasApproximateUserBase |
P3846
|
FINISHED |
| Object | hundreds of thousands of registered 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: hundreds of thousands of registered users | Statement: [Undernet, hasApproximateUserBase, hundreds of thousands of registered users]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateUserBase Context triple: [Undernet, hasApproximateUserBase, hundreds of thousands of registered users]
-
A.
approximateAudienceSize
chosen
Indicates an estimated number of individuals or entities that are expected to be reached or affected in a given context.
-
B.
hasApproximateNativeSpeakers
Indicates that an entity is associated with an estimated or approximate number of people who speak it as their native language.
-
C.
hasPopulationApproximate
Indicates that an entity has an estimated or approximate population size, rather than an exact count.
-
D.
audienceSizeApproximate
Indicates an estimated or approximate number of people in the audience for an event or content.
-
E.
hasApproximateAdherents
Indicates that an entity is associated with a non-exact, estimated number of adherents or followers.
- 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_69ca848e80748190b91d1e04d35512c7 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec56d944819081bc6ea36c905ba2 |
completed | April 2, 2026, 4:11 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba795808190acc9124c98c6e40f |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:09 p.m.