Triple
T38672273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snow |
E943627
|
entity |
| Predicate | meltsAt |
P19716
|
FINISHED |
| Object | 0 °C at standard pressure |
—
|
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: 0 °C at standard pressure | Statement: [Snow, meltsAt, 0 °C at standard pressure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meltsAt Context triple: [Snow, meltsAt, 0 °C at standard pressure]
-
A.
meltingPoint
chosen
Indicates the temperature at which a substance changes from solid to liquid under specified conditions.
-
B.
meltingProperty
Indicates that one entity has the capacity or tendency to melt another entity under certain conditions.
-
C.
meltsIn
Indicates that one substance transitions from solid to liquid when placed in or exposed to another specified substance.
-
D.
canMelt
Indicates that one entity has the capability to melt another entity or substance under appropriate conditions.
-
E.
heatOfFusion
Indicates the amount of energy required to change a substance from solid to liquid at constant temperature and pressure.
- 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_69f76eec28708190b9c82a505fc278e0 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:33 p.m.