Triple
T12070113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dulong–Petit law |
E287400
|
entity |
| Predicate | lessAccurateAt |
P62233
|
FINISHED |
| Object | low temperatures |
—
|
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: low temperatures | Statement: [Dulong–Petit law, lessAccurateAt, low temperatures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lessAccurateAt Context triple: [Dulong–Petit law, lessAccurateAt, low temperatures]
-
A.
hasAccuracy
chosen
Indicates that something possesses a specified level or measure of correctness, precision, or exactness in relation to a standard or reference.
-
B.
lessEffectiveAt
Indicates that one entity has a reduced ability or lower level of success in performing, influencing, or achieving a particular action or outcome compared to another.
-
C.
accuracyDependsOn
Indicates that the accuracy of one entity or process is contingent upon, or influenced by, another entity or factor.
-
D.
lessFeatureRichThan
Indicates that one entity has fewer or less advanced features or capabilities than another entity.
-
E.
isLessAccessibleThan
Indicates that one entity can be reached, used, or understood with more difficulty or under more constraints 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bda47c8190b94860b31df4a98c |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:48 p.m.