Triple
T22666559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poisson’s ratio |
E559806
|
entity |
| Predicate | zeroValueMeans |
P9150
|
FINISHED |
| Object | no lateral strain under axial 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: no lateral strain under axial loading | Statement: [Poisson’s ratio, zeroValueMeans, no lateral strain under axial loading]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: zeroValueMeans Context triple: [Poisson’s ratio, zeroValueMeans, no lateral strain under axial loading]
-
A.
zeroDefinition
Indicates that something has no defined value, quantity, or specification within the given context.
-
B.
isZeroFor
chosen
Indicates that a given value, expression, or function evaluates to zero when applied to or considered with respect to a specified entity or context.
-
C.
emptyValueMeaning
Indicates that a value is intentionally left empty to convey a specific, meaningful state rather than simply missing data.
-
D.
zeroConcept
Indicates a conceptual or abstract entity that has no concrete instances or realizations in the given context.
-
E.
absoluteZeroValue
Indicates that a quantity, measurement, or parameter is exactly at absolute zero, the lowest possible value in its defined scale.
- 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_69e2454a158c819093b8e35f5045efb6 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1781c2c808190baf6964ca1eced6f |
completed | April 29, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69ee62a6245881909506ff502da14137 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:09 p.m.