Triple
T1535784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berry–Esseen theorem |
E32545
|
entity |
| Predicate | errorTermOrder |
P29588
|
FINISHED |
| Object | O(1∕√n) |
—
|
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: O(1∕√n) | Statement: [Berry–Esseen theorem, errorTermOrder, O(1∕√n)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: errorTermOrder Context triple: [Berry–Esseen theorem, errorTermOrder, O(1∕√n)]
-
A.
orderPrecedence
Indicates that one entity must come before another in a defined sequence or priority order.
-
B.
canonicalOrderEnd
Indicates the point or boundary at which a defined canonical or standard ordering of elements, events, or components concludes.
-
C.
maximumConsecutiveTerms
Indicates the greatest number of terms that can occur in an unbroken, continuous sequence within a given context or structure.
-
D.
hasRankOrder
Indicates that one entity is ordered or positioned relative to others according to a specific ranking or sequence.
-
E.
subsequentOrder
Indicates that one order occurs after or follows another order in sequence.
- 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_69a885ea86308190998f6bc14bb91f8e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a915f323bc8190aa757142c225e0ae |
completed | March 5, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69a907b046448190be8ea4d7b20255f7 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69a915f1694081908f87b509eda1309f |
completed | March 5, 2026, 5:34 a.m. |
Created at: March 4, 2026, 7:26 p.m.