Triple
T36704171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Potts glass |
E906309
|
entity |
| Predicate | studiedAsModelFor |
P28233
|
FINISHED |
| Object | structural glass behavior |
—
|
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: structural glass behavior | Statement: [Potts glass, studiedAsModelFor, structural glass behavior]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: studiedAsModelFor Context triple: [Potts glass, studiedAsModelFor, structural glass behavior]
-
A.
isModelOf
chosen
Indicates that one entity serves as a representation or abstraction that captures the structure or behavior of another entity.
-
B.
studiedBy
Indicates that a subject (such as a field, topic, or object) is examined, researched, or learned by an agent (such as a person or group).
-
C.
isModelledAfter
Indicates that one entity is created, designed, or structured based on the form, features, or principles of another entity.
-
D.
modeledWith
Indicates that something is represented, simulated, or described using a particular model, method, or modeling technique.
-
E.
hasStudyModel
Indicates that an entity is associated with, or defined by, a particular study model used for analysis, simulation, or representation.
- 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_69f76e7195c48190b5580c9cfb01e95f |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c80d4ba48190bf6beb2c9b108be1 |
completed | May 3, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69f7c4796ebc819084a0dc08505e5f14 |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:12 p.m.