Triple
T25493175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taylor–Couette flow |
E638887
|
entity |
| Predicate | hasBaseState |
P162586
|
FINISHED |
| Object | circular Couette flow |
—
|
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: circular Couette flow | Statement: [Taylor–Couette flow, hasBaseState, circular Couette flow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBaseState Context triple: [Taylor–Couette flow, hasBaseState, circular Couette flow]
-
A.
hasCoreState
Indicates that an entity possesses or is associated with a fundamental or primary state that defines its core condition or behavior.
-
B.
hasStateBranch
Indicates that one entity functions as a branch, subdivision, or local office of a larger parent entity within a particular state or regional jurisdiction.
-
C.
hasBaseField
Indicates that one entity serves as the foundational or underlying field structure upon which another entity is defined or constructed.
-
D.
hasBaseCount
Indicates the number of base units or fundamental components associated with an entity.
-
E.
hasStateSystem
Indicates that an entity possesses, follows, or is governed by a particular system of state organization, rules, or governance.
- 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_69e75dbbd2a88190b70e1e645de14b9a |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f62b9e5ba88190a3c0d46edec7afe7 |
completed | May 2, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69f623a4e1048190bbb8dd1253fdcee9 |
completed | May 2, 2026, 4:17 p.m. |
| PDg | Predicate description generation | batch_69f627ad6d4c81909796d39d78e414f9 |
completed | May 2, 2026, 4:34 p.m. |
Created at: April 21, 2026, 2:39 p.m.