Triple
T23737939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | heterotic supergravity |
E586586
|
entity |
| Predicate | frameOftenUsed |
P124922
|
FINISHED |
| Object | string frame |
—
|
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: string frame | Statement: [heterotic supergravity, frameOftenUsed, string frame]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frameOftenUsed Context triple: [heterotic supergravity, frameOftenUsed, string frame]
-
A.
frequentUseCase
Indicates a situation, scenario, or pattern of use that occurs regularly or more often than others in relation to the subject.
-
B.
framesAs
Indicates how one entity presents, characterizes, or interprets another entity or situation in a particular light or context.
-
C.
frame
Indicates placing or presenting something within a particular context, structure, or perspective that shapes how it is interpreted.
-
D.
usesFrame
chosen
Indicates that one entity employs, relies on, or is structured around a particular frame, framework, or reference structure provided by another entity.
-
E.
isMoreFrequentlyUsedThan
Indicates that one entity is used or occurs with greater frequency than another entity.
- 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_69e24907dc9c8190be074c9c96a0ec2d |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1bad356c88190ae29ce403145ee73 |
completed | April 29, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69f155f012808190a4b1cbc155558ade |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 7:11 p.m.