Triple
T19377065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sr2CuO2Cl2 |
E484698
|
entity |
| Predicate | isModelSystemFor |
P28233
|
FINISHED |
| Object | spin-charge separation studies |
—
|
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: spin-charge separation studies | Statement: [Sr2CuO2Cl2, isModelSystemFor, spin-charge separation studies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isModelSystemFor Context triple: [Sr2CuO2Cl2, isModelSystemFor, spin-charge separation studies]
-
A.
isModelOf
chosen
Indicates that one entity serves as a representation or abstraction that captures the structure or behavior of another entity.
-
B.
modelsSystemsWith
Indicates that one entity creates or uses a representation or abstraction to describe, analyze, or simulate another system.
-
C.
usesModelsType
Indicates that one entity employs or relies on a specific type or category of models in its operation or behavior.
-
D.
possibleModel
Indicates that one entity can serve as a potential or candidate model or template for another entity.
-
E.
supportsModelingOf
Indicates that one entity provides the capability or functionality needed to represent, simulate, or model another entity or process.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61a5cfbf48190ac60e3ffa6baa263 |
completed | April 20, 2026, 12:21 p.m. |
| PD | Predicate disambiguation | batch_69e4fd54f8e48190956e73dd8969164a |
completed | April 19, 2026, 4:05 p.m. |
Created at: April 10, 2026, 1:35 p.m.