Triple
T22666567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poisson’s ratio |
E559806
|
entity |
| Predicate | usedToRelate |
P149157
|
FINISHED |
| Object | Young’s modulus and shear modulus |
—
|
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: Young’s modulus and shear modulus | Statement: [Poisson’s ratio, usedToRelate, Young’s modulus and shear modulus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedToRelate Context triple: [Poisson’s ratio, usedToRelate, Young’s modulus and shear modulus]
-
A.
mayRelateTo
Indicates a possible, but not certain, relationship or association between two entities.
-
B.
allyRelation
Indicates a cooperative, supportive relationship in which the entities act as allies toward shared or aligned goals.
-
C.
subjectRelation
Indicates that one entity stands in a specified relational role or connection to another entity.
-
D.
conditionRelatesTo
Indicates that one condition is relevant, connected, or applicable to another condition or contextual factor.
-
E.
laterRelationWith
Indicates that one entity stands in a temporal relationship to another such that it occurs or exists at a later time than the other.
- 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_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. |
| PDg | Predicate description generation | batch_69ee8843d3308190b6e22bb98ae5c3d8 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 17, 2026, 3:09 p.m.