Triple
T18479105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | fundamental theorem of arithmetic |
E451510
|
entity |
| Predicate | yearFormalized |
P131810
|
FINISHED |
| Object | 1801 |
—
|
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: 1801 | Statement: [fundamental theorem of arithmetic, yearFormalized, 1801]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearFormalized Context triple: [fundamental theorem of arithmetic, yearFormalized, 1801]
-
A.
yearTaken
Indicates the specific calendar year in which an action, event, or record associated with the subject was carried out or occurred.
-
B.
ordinationYear
Indicates the year in which an individual was formally ordained to a religious office or role.
-
C.
formedInYear
Indicates the year in which an entity was originally established, created, or came into existence.
-
D.
yearType
Indicates the classification or category assigned to a specific year (e.g., academic, fiscal, calendar, leap).
-
E.
yearDescribedAs
Indicates the specific year in which something was formally characterized, documented, or described.
- F. None of above. chosen
Provenance (4 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_69d8d38465a0819099b9b42d2a662ac1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53065e8388190bb216dae89f8cf75 |
completed | April 19, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69e469d671088190b619de96ea6f92ab |
completed | April 19, 2026, 5:36 a.m. |
| PDg | Predicate description generation | batch_69e46d2aa72c8190a40854a7a52081e2 |
completed | April 19, 2026, 5:50 a.m. |
Created at: April 10, 2026, 11:35 a.m.