Triple
T31593487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TNT |
E806161
|
entity |
| Predicate | hasMeltingCastingAdvantage |
P196465
|
FINISHED |
| Object | can be safely melted and poured into shells |
—
|
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: can be safely melted and poured into shells | Statement: [TNT, hasMeltingCastingAdvantage, can be safely melted and poured into shells]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeltingCastingAdvantage Context triple: [TNT, hasMeltingCastingAdvantage, can be safely melted and poured into shells]
-
A.
materialMelted
Indicates that a material has undergone melting, transitioning from a solid to a liquid state.
-
B.
hasMeltingMechanism
Indicates that an entity possesses a specific mechanism or process by which it melts or causes melting.
-
C.
canMelt
Indicates that one entity has the capability to melt another entity or substance under appropriate conditions.
-
D.
meltingProperty
Indicates that one entity has the capacity or tendency to melt another entity under certain conditions.
-
E.
meltingQuality
Indicates the degree or manner in which something melts, such as how easily, quickly, or smoothly it transitions from solid to liquid.
- 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_69f348d4891c8190b02bae3c8ecb68b7 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe38be079c8190a240191ac0e73e3a |
completed | May 8, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69fe350344508190930de2218156ca02 |
completed | May 8, 2026, 7:09 p.m. |
| PDg | Predicate description generation | batch_69fe38bc3e9c8190838430b22b82503f |
completed | May 8, 2026, 7:25 p.m. |
Created at: April 30, 2026, 10:29 p.m.