Triple
T14636277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Water |
E343615
|
entity |
| Predicate | heatOfFusion |
P115139
|
FINISHED |
| Object | about 6.01 kJ/mol |
—
|
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: about 6.01 kJ/mol | Statement: [Water, heatOfFusion, about 6.01 kJ/mol]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: heatOfFusion Context triple: [Water, heatOfFusion, about 6.01 kJ/mol]
-
A.
meltingPoint
Indicates the temperature at which a substance changes from solid to liquid under specified conditions.
-
B.
hasMeltingMechanism
Indicates that an entity possesses a specific mechanism or process by which it melts or causes melting.
-
C.
heatFlow
Indicates the transfer of thermal energy from one entity or region to another due to a temperature difference.
-
D.
boilingPoint
Indicates the temperature at which a substance changes from liquid to gas under specified pressure conditions.
-
E.
canMelt
Indicates that one entity has the capability to melt another entity or substance under appropriate conditions.
- 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_69d822dffc3c8190aa173b90761bffda |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4ab9578819085b4cf7244d30d87 |
completed | April 14, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69de657359c88190b082e3e9f86fc1d7 |
completed | April 14, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69de716c17cc8190aeb85296abee85a7 |
completed | April 14, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:26 a.m.