Triple
T9251216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nupedia |
E222326
|
entity |
| Predicate | articleCountInProgressAtClosure |
P64750
|
FINISHED |
| Object | about 150 |
—
|
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 150 | Statement: [Nupedia, articleCountInProgressAtClosure, about 150]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: articleCountInProgressAtClosure Context triple: [Nupedia, articleCountInProgressAtClosure, about 150]
-
A.
articleCount
Indicates the number of articles associated with a given entity or context.
-
B.
articleCountApprox
chosen
Indicates that the relationship specifies an approximate number of articles associated with an entity.
-
C.
subjectToClosure
Indicates that an entity is liable or scheduled to be closed, discontinued, or shut down under certain conditions or plans.
-
D.
closureFrequency
Indicates how often a particular process, event, or entity is closed or brought to an end within a given period.
-
E.
sectionCountApproximate
Indicates that the number of sections associated with an entity is known only approximately rather than as an exact count.
- 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_69ca841d2b18819089f9faf5b2c2aec0 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd05f9ade48190ac8425a1c6f066b1 |
completed | April 1, 2026, 11:48 a.m. |
| PD | Predicate disambiguation | batch_69cc7a4e79e48190b3200247f4624867 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:31 p.m.