Triple
T18573013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Curie–Weiss law |
E453915
|
entity |
| Predicate | improvesDescriptionNear |
P6555
|
FINISHED |
| Object | ferromagnetic phase transition |
—
|
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: ferromagnetic phase transition | Statement: [Curie–Weiss law, improvesDescriptionNear, ferromagnetic phase transition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: improvesDescriptionNear Context triple: [Curie–Weiss law, improvesDescriptionNear, ferromagnetic phase transition]
-
A.
improvesOn
chosen
Indicates that one entity enhances, refines, or performs better than another entity, typically by addressing its limitations or increasing its effectiveness.
-
B.
definedNear
Indicates that one entity is defined in close spatial or contextual proximity to another entity.
-
C.
improvesAccessToward
Indicates that one entity enhances or facilitates the ability of another entity to reach, use, or benefit from a resource, service, or opportunity.
-
D.
near
Indicates that one entity is located at a short distance from another entity in space or position.
-
E.
meetsNear
Indicates that two entities meet or come together at a location that is in close proximity to a specified reference point or area.
- 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e543c7f63c81909b5d5764ffd20234 |
completed | April 19, 2026, 9:06 p.m. |
| PD | Predicate disambiguation | batch_69e478c98d4c81909d37a0e72c6e7bd0 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:43 a.m.