Triple
T22666572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poisson’s ratio |
E559806
|
entity |
| Predicate | typicalValueForCork |
P99172
|
FINISHED |
| Object | close to 0 |
—
|
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: close to 0 | Statement: [Poisson’s ratio, typicalValueForCork, close to 0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalValueForCork Context triple: [Poisson’s ratio, typicalValueForCork, close to 0]
-
A.
hasCorkscrew
Indicates that one entity possesses or is equipped with a corkscrew.
-
B.
typicalValueFor
chosen
Indicates that one entity represents a standard, representative, or commonly occurring value associated with another entity.
-
C.
typicalCaskType
Indicates the usual or most commonly used type of cask associated with a given entity or context.
-
D.
typicalValueForAluminum
Indicates the standard or commonly accepted value (such as a property or parameter) that is characteristic for aluminum in a given context.
-
E.
typicalCapacity
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
- 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.