Triple
T10991465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Simpson's rule |
E259761
|
entity |
| Predicate | textbookTopicIn |
P34305
|
FINISHED |
| Object | introductory numerical analysis courses |
—
|
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: introductory numerical analysis courses | Statement: [Simpson's rule, textbookTopicIn, introductory numerical analysis courses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textbookTopicIn Context triple: [Simpson's rule, textbookTopicIn, introductory numerical analysis courses]
-
A.
notableTextbook
Indicates that a textbook is recognized as significant, influential, or widely used within its field or subject area.
-
B.
book4Subject
chosen
Indicates that something is the subject or topic that a particular book is about.
-
C.
book3Subject
Indicates that an entity serves as the third subject or topic discussed or treated in a particular book.
-
D.
book2Subject
Indicates that an entity serves as the subject or topic that a given book is about.
-
E.
widelyStudiedIn
Indicates that something has been extensively researched, analyzed, or examined within a particular field, domain, or context.
- 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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d795d1e918819090c71f5a077fa15a |
completed | April 9, 2026, 12:04 p.m. |
| PD | Predicate disambiguation | batch_69d72e93ac648190b46c5d12bf3eb1e9 |
completed | April 9, 2026, 4:44 a.m. |
Created at: April 8, 2026, 9:24 p.m.