Triple
T22593169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Leicester cheese |
E565001
|
entity |
| Predicate | meltingProperty |
P148857
|
FINISHED |
| Object | good melting cheese |
—
|
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: good melting cheese | Statement: [Red Leicester cheese, meltingProperty, good melting cheese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meltingProperty Context triple: [Red Leicester cheese, meltingProperty, good melting cheese]
-
A.
meltingPoint
Indicates the temperature at which a substance changes from solid to liquid under specified conditions.
-
B.
heatOfFusion
Indicates the amount of energy required to change a substance from solid to liquid at constant temperature and pressure.
-
C.
canMelt
Indicates that one entity has the capability to melt another entity or substance under appropriate conditions.
-
D.
materialMelted
Indicates that a material has undergone melting, transitioning from a solid to a liquid state.
-
E.
hasMeltingMechanism
Indicates that an entity possesses a specific mechanism or process by which it melts or causes melting.
- 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_69e245836014819091b91ed3074742a3 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f16163cb248190b377b110d80a6730 |
completed | April 29, 2026, 1:39 a.m. |
| PD | Predicate disambiguation | batch_69ee627be4248190889a88764624e174 |
completed | April 26, 2026, 7:07 p.m. |
| PDg | Predicate description generation | batch_69ee8841e9cc81908d23b34215e3be71 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 17, 2026, 2:49 p.m.