Triple
T58779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Feynman Lectures on Physics |
E1163
|
entity |
| Predicate | isWidelyUsedAs |
P2506
|
FINISHED |
| Object | supplementary text in university physics 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: supplementary text in university physics courses | Statement: [Feynman Lectures on Physics, isWidelyUsedAs, supplementary text in university physics courses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isWidelyUsedAs Context triple: [Feynman Lectures on Physics, isWidelyUsedAs, supplementary text in university physics courses]
-
A.
isUsedAs
chosen
Indicates that one entity serves a particular function, role, or purpose as another entity.
-
B.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
C.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
-
D.
isMostWidelyUsedWritingSystem
Indicates that the subject writing system is used by more people or in more contexts than any other writing system.
-
E.
usedInDomain
Indicates that something (such as a concept, method, or resource) is applied or utilized within a particular domain or field.
- 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_69a24a552ef88190a0df287d68c65cba |
completed | Feb. 28, 2026, 1:52 a.m. |
| NER | Named-entity recognition | batch_69a250e401288190ba12322c9c5f07c9 |
completed | Feb. 28, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69a24e9f40908190a2f4a2111469b733 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 1:55 a.m.