Triple
T26246243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portevin–Le Chatelier effect |
E656452
|
entity |
| Predicate | observedUnder |
P34153
|
FINISHED |
| Object | uniaxial tensile loading |
—
|
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: uniaxial tensile loading | Statement: [Portevin–Le Chatelier effect, observedUnder, uniaxial tensile loading]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: observedUnder Context triple: [Portevin–Le Chatelier effect, observedUnder, uniaxial tensile loading]
-
A.
observedBy
Indicates that an entity is perceived, monitored, or recorded by another entity acting as the observer.
-
B.
observedVia
Indicates that something is perceived, detected, or measured through a particular medium, instrument, method, or channel.
-
C.
observedFor
Indicates that one entity is monitored, watched, or examined over a period of time for the benefit or analysis of another entity.
-
D.
observedAs
Indicates that one entity is perceived, recorded, or identified in the role, state, or form of another entity.
-
E.
isObservedIn
chosen
Indicates that something (such as a phenomenon, property, or behavior) is detected, recorded, or found to occur within a particular context, setting, or environment.
- 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_69ee5b4c59a881909d9ee4fd013fffd5 |
completed | April 26, 2026, 6:37 p.m. |
| NER | Named-entity recognition | batch_69f6430a93a48190854ce71df680b2fa |
completed | May 2, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69f641da05b881909f6283c988639c53 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 26, 2026, 9:05 p.m.