Triple
T36704170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Potts glass |
E906309
|
entity |
| Predicate | hasDisorderType |
P200074
|
FINISHED |
| Object | quenched random interactions |
—
|
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: quenched random interactions | Statement: [Potts glass, hasDisorderType, quenched random interactions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDisorderType Context triple: [Potts glass, hasDisorderType, quenched random interactions]
-
A.
hasAssociatedDisease
Indicates that an entity is linked to, or commonly occurs with, a particular disease or medical condition.
-
B.
diagnosedWith
Indicates that a subject has been identified, typically by a medical professional, as having a particular disease or medical condition.
-
C.
exampleOfDisorder
Indicates that one entity is an instance or specific case of a particular disorder represented by another entity.
-
D.
hasTypicalConditions
Indicates that something is associated with conditions or circumstances that are commonly or normally present for it.
-
E.
hasDiagnosticCriterion
Indicates that a specific diagnostic criterion is used to define, identify, or determine the presence of a particular condition, disorder, or classification.
- 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_69f76e7195c48190b5580c9cfb01e95f |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff6fba1a5c8190a660279a6271d785 |
completed | May 9, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69ff6f59388c8190a7d6ab7bc7705bc0 |
completed | May 9, 2026, 5:31 p.m. |
| PDg | Predicate description generation | batch_69ff6fb9691c819082ee2f3c648b7dc1 |
completed | May 9, 2026, 5:32 p.m. |
Created at: May 3, 2026, 4:12 p.m.