Triple
T130665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Does the Inertia of a Body Depend Upon Its Energy Content? |
E2646
|
entity |
| Predicate | languageFeature |
P5192
|
FINISHED |
| Object | non-technical, concise exposition |
—
|
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: non-technical, concise exposition | Statement: [Does the Inertia of a Body Depend Upon Its Energy Content?, languageFeature, non-technical, concise exposition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageFeature Context triple: [Does the Inertia of a Body Depend Upon Its Energy Content?, languageFeature, non-technical, concise exposition]
-
A.
programmingLanguage
Indicates that one entity is a programming language used to create, control, or interact with the other entity.
-
B.
languageBranch
Indicates that one language belongs to, or is classified under, a broader linguistic branch or subgroup.
-
C.
languageOfOperation
Indicates the language in which an entity (such as a system, service, or process) primarily operates or functions.
-
D.
supportsFeature
Indicates that one entity provides, enables, or is compatible with a particular feature or capability of another.
-
E.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
- 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257845c548190bfb49409988d1c57 |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2564da96c8190aa8204de25229c15 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a256c72f6c81909b619b90d829d86e |
completed | Feb. 28, 2026, 2:45 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.