Triple
T18371203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Verdet constant |
E446183
|
entity |
| Predicate | isMaterialSpecific |
P130862
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Verdet constant, isMaterialSpecific, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMaterialSpecific Context triple: [Verdet constant, isMaterialSpecific, true]
-
A.
materialSpecialization
Indicates a relationship where one material is a specialized, more specific, or refined form of another more general material.
-
B.
usesMaterialBy
Indicates that one entity makes use of or employs a material that is provided, specified, or created by another entity.
-
C.
hasMaterialType
Indicates that something is composed of, made from, or characterized by a specific type of material.
-
D.
hasMaterialAspect
Indicates that something possesses a physical or tangible component or aspect as part of its overall nature or existence.
-
E.
featuresMaterialType
Indicates that an entity is characterized by or incorporates a specific type of material.
- 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_69d8b9f370b88190b1e5081c2c238e7f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e5175324e48190a00572e15423feb7 |
completed | April 19, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69e44fed3fdc81908f4ed6a81db42416 |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e451a1bda48190a9cd1db436d4be62 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 10:44 a.m.