Triple
T36390401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ice Palace in Quebec City |
E896310
|
entity |
| Predicate | meltsIn |
P185426
|
FINISHED |
| Object | spring |
—
|
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: spring | Statement: [Ice Palace in Quebec City, meltsIn, spring]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meltsIn Context triple: [Ice Palace in Quebec City, meltsIn, spring]
-
A.
canMelt
Indicates that one entity has the capability to melt another entity or substance under appropriate conditions.
-
B.
hasMeltingMechanism
Indicates that an entity possesses a specific mechanism or process by which it melts or causes melting.
-
C.
meltingProperty
Indicates that one entity has the capacity or tendency to melt another entity under certain conditions.
-
D.
materialMelted
Indicates that a material has undergone melting, transitioning from a solid to a liquid state.
-
E.
isNonMelting
Indicates that the subject does not melt or transition to a liquid state under the relevant or specified 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_69f76e52e3108190becf70b090ae7bd6 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bcccd7988190aa5c931ff347d33c |
completed | May 3, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69f7be9b9ab481908328e0e8d8ac73d4 |
completed | May 3, 2026, 9:31 p.m. |
Created at: May 3, 2026, 4:10 p.m.